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Passive compliant module with the displacement measurement sensor and its application for automatic assembly
12th IFAC Symposium on Robot Control Budapest, Hungary, August 27-30, 2018 12th IFAC Symposium on Robot Control Budapest, Hungary, August 27-30, 2018 12th IFAC Symposium on Robot Control Available online at www.sciencedirect.com Budapest, Hungary, August 27-30, 2018 12th IFAC Symposium on Robot Control Budapest, Hungary, August 27-30, 2018 Budapest, Hungary, August 27-30, 2018
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IFAC PapersOnLine 85–90 Passive compliant module with 51-22 the (2018) displacement measurement sensor Passive compliant module with the displacement measurement sensor Passive module with measurement and its application fordisplacement automatic assembly Passive compliant compliant module with the the measurement sensor sensor and its application fordisplacement automatic assembly Passive compliant module with the displacement measurement sensor and its application for automatic assembly and its application forTaeyong automatic assembly Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Choi*. Jongwoo Park* and Byungin Kim* and its application forTaeyong automatic assembly Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Choi*. Jongwoo Park* and Byungin Kim*
Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Taeyong Choi*. Jongwoo Park* and Byungin Kim* Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Taeyong Choi*. Jongwoo Park* and Byungin Kim* Dong Il Park1*. HwisuofKim*. Chanhun Park*. Taeyong Jongwoo Park*&and Byungin Kim* * Department Robotics and Mechatronics, KoreaChoi*. Institute of Machinery Materials * Department of Robotics and +82-42-868-7984; Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: e-mail:[email protected]) * Department of Robotics and +82-42-868-7984; Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: e-mail:[email protected]) * Department of Robotics and Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: +82-42-868-7984; e-mail:[email protected]) * Department of Robotics and +82-42-868-7984; Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: e-mail:[email protected]) Korea (Tel: +82-42-868-7984; e-mail:[email protected]) Abstract: Robot Daejeon, manipulators have been applied in the various automated manufacturing for handling, Abstract: Robot manipulators have been deburring, applied in simple the various automated for handling, transferring, welding, polishing, painting, assembly and so manufacturing on. Robotic assembly of the Abstract: Robot manipulators have been deburring, applied in simple the various automated manufacturing for handling, transferring, welding, polishing, painting, assembly and so on. Robotic assembly of the Abstract: Robot manipulators havethebeen applied inthethe various automated manufacturing for handling, precision parts is difficult because accuracy of robot manipulator is not enough and the teaching transferring, welding, polishing, painting, deburring, simple assembly and is sonot on. enough Roboticand assembly of the Abstract: Robot have applied the various automated manufacturing precision is manipulators difficult because thebeen accuracy ofinthe robot manipulator the teaching transferring, welding, polishing, painting, deburring, simple assembly and soassembly on. Robotic assembly of the procedureparts is complex. There have been various technologies about robotic such asfor thehandling, position precision parts is difficult because the accuracy of the robot manipulator is not enough and the teaching transferring, polishing, painting, deburring, simple andwith soassembly on. Robotic assembly of the procedure is welding, complex. There have been various technologies about robotic such as the the teaching position precision parts isstrategy, difficult because thetorque accuracy of the robotassembly manipulator is not enough and based assembly the active feedback control algorithm FT sensor or joint torque procedure is complex. There have been various technologies about robotic assembly such as the the teaching position precision parts is difficult because the accuracy of the robot manipulator is not enough and based assembly strategy, the active torque feedback control algorithm with FT sensor or joint torque procedure is complex. There have been various technologies about robotic assembly such as the position sensorsassembly and the remote center compliance which gives the passive compliance to the end-effector. In the based strategy, thehave active torque feedback algorithm with FT sensor or torque procedure isthe complex. There been various technologies about robotic assembly such as joint the position sensors andproposed remote center compliance which givescontrol thedevice passive compliance to the end-effector. InThe the based assembly strategy, the active torque feedback control algorithm with FT sensor or joint torque paper, we a new type of the passive compliant which can measure its deformation. sensorsassembly andproposed the remote center compliance which givescontrol thedevice passive compliance to the end-effector. InThe the based strategy, the active torque feedback algorithm with FT sensor or joint torque paper, we a new type of the passive compliant which can measure its deformation. sensors and the remote center compliance which gives the passive compliance to the end-effector. In the proposed device, which is type calledof“Magic Gripper”, is composed of thecan passive compliance module,The paper, we proposed a new the passive compliant device which measure itsend-effector. deformation. sensors and the remote center compliance which gives the passive compliance to the In proposed device, which is called “Magic Gripper”, is composed of the passive compliance module, the paper, we module, proposedthe a new type of the measurement passive compliant device which can measure its deformation. The gripping displacement module and the controller module. Also, a new proposed device, which is type calledof“Magic Gripper”, is composed of thecontroller passive compliance module, the paper, we module, proposed a new the measurement passive compliant device measure its deformation. The gripping the displacement module and the module. Also, a new proposed device, which isthe called “Magic Gripper”, is composed of thecan passive compliance module, the assembly strategy using passive compliant device with thewhich displacement measurement system is gripping module, the displacement measurement module and the controller module. Also, a new proposed device, which isdevice called “Magic Gripper”, is composed thecontroller passive compliance module, the assembly strategy usingdisplacement the passive compliant device with and the of displacement measurement system is gripping module, the measurement module the module. Also, a new proposed. The proposed and the proposed assembly strategy are proved to be very useful for assembly strategy usingdisplacement the passive compliant device with and the the displacement system is gripping the measurement module controller module. Also, a new proposed. The proposed andparts. the proposed assembly are provedmeasurement to be very useful for assembly strategy using the passive compliant device with strategy the displacement measurement system is automaticmodule, assembly of thedevice precision proposed. The proposed device and the proposed assembly strategy are proved to be very useful for assembly using the passive compliant device with strategy the displacement systemfor is automatic assembly of thedevice precision proposed. strategy The proposed andparts. the proposed assembly are provedmeasurement to be very useful automatic assembly of thedevice precision © 2018, IFAC (International Federation of Automatic by Elsevier Ltd. proposed. The proposed andparts. the proposed assembly strategy are proved toAllberights veryreserved. useful for Keywords: Robotic assembly, Automatic assembly,Control) RemoteHosting center compliance, Magic gripper, Passive automatic assembly of the precision parts. Keywords: Robotic of assembly, Automatic automatic the precision parts. assembly, Remote center compliance, Magic gripper, Passive complianceassembly Keywords: assembly, Automatic assembly, Remote center compliance, Magic gripper, Passive compliance Robotic Keywords: Robotic assembly, Automatic assembly, Remote center compliance, Magic gripper, Passive compliance Robotic assembly, Automatic assembly, Remote center compliance, Magic gripper, Passive Keywords: compliance compliance of a robot to estimate the system state and to increase the 1. INTRODUCTION of a robot to the task. system state kinds and to ofincrease the robustness of estimate assembly These assembly 1. INTRODUCTION of a robot to estimate the task. system state kinds and to ofincrease the robustness of assembly These assembly a robot to estimate the system state andsystematical to increase and the INTRODUCTION algorithms make the assembly state to be Robot manipulators1. have been applied in the various of robustness of assembly task. These kinds of assembly 1. INTRODUCTION of a robot to estimate the task. system state andsuccess to ofincrease the make the assembly state tothe be systematical and Robot manipulators have been applied in the welding, various algorithms robustness ofand assembly These kinds assembly hierarchical obviously increase rates of 1. INTRODUCTION automated manufacturing for handling, transferring, make the assembly state tothe be systematical and Robot manipulators have been applied in the welding, various algorithms robustness of assembly task. These kinds of assembly hierarchical and obviously increase success rates of automated manufacturing for handling, transferring, algorithms make the assembly state to be systematical and assembly task by classifying the assembly states Robot manipulators have been applied in the various polishing, painting, deburring, simple assembly and so on. hierarchical and by obviously increase the success ratesand of automated manufacturing for been handling, transferring, welding, algorithms make the assembly state to be systematical assembly task classifying the assembly states Robot manipulators have applied in the various polishing, painting, deburring, simple assembly and so on. hierarchical and obviously increase the success rates of monitoring the by current assemblythestates. However, these automated manufacturing forcan handling, transferring, welding, These kindspainting, of applications be implemented by the robot assembly task classifying assembly states and polishing, deburring, simple assembly and so on. hierarchical and obviously increase the success rates of monitoring the current assembly states. However, these automated manufacturing for handling, transferring, welding, These kinds of applications can be implemented by the robot assembly task by classifying the assembly states and algorithms cannot reduce the effort and time for the teaching polishing, painting, deburring, simple assembly and sotask. on. monitoring the current assembly states. However, these programming orapplications robot teaching for the simple repetitive These kinds of can be implemented by the robot assembly task by classifying the assembly states and algorithms cannot reduce the effort and time for the teaching polishing, deburring, simple assembly and sorobot on. programming robot teaching thethe simple repetitive task. the current assemblythestates. However, process andcannot cannot compensate position ofthese the These kindspainting, oforapplications can for beofimplemented by the However, automatic precision parts is monitoring algorithms reduce the effortthe and time However, for error the teaching programming orapplications robot assembly teaching for thethe simple repetitive task. monitoring the current assembly states. process andcannot cannot compensate position error ofthese the These kinds of can be implemented by the robot However, automatic assembly of precision parts is algorithms reduce the effort and time for the teaching taught trajectory in the repetitive playback phase. programming or robot teaching for the simple repetitive task. difficult because of theassembly accuracy ofof the robot manipulator and process andcannot cannot compensate the position error of the However, automatic precision parts is algorithms reduce the effort and time for the teaching taught trajectory in the repetitive playback phase. programming or robot teaching for the simple repetitive task. difficult because of theprocedure. accuracy ofof the robot manipulator and cannot compensate the position error of the However, automatic assembly precision partsand is process the complex teaching taught trajectory in(2006) the repetitive phase. difficult because of theprocedure. accuracy ofofthethe robot manipulator process and cannot the fusion position of and the Stemmer et al. studied playback the oferror vision However, automatic precision partsand is taught the complex teaching trajectory in thecompensate repetitive playback phase. difficult because of theassembly accuracy of the robot manipulator and Stemmer et al. (2006) studied the fusion of vision and the complex teaching procedure. taught trajectory in the repetitive playback phase. force/torque information for robotic assembly tasks. The difficult because of the accuracy of the robot manipulator and Various assembly strategies with the assembly state Stemmer et information al. (2006) studied the fusion of vision and the complex teaching procedure. for robotic assembly tasks. The Various assembly strategies the with assembly state force/torque Stemmer et al. the afusion vision and vision system was(2006) used tostudied determine global of initial position the complex teaching procedure. with estimation, active compliance control the force force/torque information for robotic assembly tasks. The Various assembly strategies with the assembly state Stemmer et al. (2006) studied the fusion of vision and vision system was used to determine a global initial position estimation, active compliance control with the force force/torque information for robotic assembly tasks. The of was the used objects. However,a global the torque feedback Various assembly strategies with the assembly state estimation controlled robot and compliance passive compliant device such as force RCC vision system to for determine initial position estimation, active control with the force/torque information robotic assembly tasks. The estimation of the objects. However, the torque feedback Various strategies with assembly state controlled robot and compliance passive compliant device such RCC system was used to be determine global initial position control algorithm had to applieda because vision based estimation, active control with theasofforce have beenassembly researched to improve the the performance the vision estimation of was the used objects. However, the torque feedback controlled robot and compliance passive compliant device such asofforce RCC vision system to be determine a because global initial position control algorithm had to applied vision based estimation, active control with the have been researched to improve the performance the estimation of the objects. However, the torque feedback position accuracy is limited. The torque controlled controlled robotThere and passive compliant device such ascontact RCC control algorithm had to be applied because visionKUKA assembly task. are several researches about the based have been researched to improve the performance of the estimation of the objects. However, the torque feedback position accuracy is limited. The torque controlled KUKA controlled robot and passive compliant device such assembly task. There aretoseveral researches about theascontact algorithm had to bewhich applied because vision based light-weight robot is is limited. used, is specially designed for have been researched improve thetask performance ofRCC the control state estimation during assembly execution. The position accuracy The torque controlled KUKA assembly task. There aretoseveral researches about the contact control algorithm had tohas bewhich applied because vision based light-weight robot isand used, isfeedback specially designed for have been researched improve the performance of the state estimation during assembly task execution. The position accuracy is limited. The torque controlled KUKA sensing joint torque torque controller. The assembly task. There are several researches about the contact perceptual data for during the contact state estimation can be various light-weight robot isand used, which isfeedback specially designed for state estimation assembly task about execution. The sensing position accuracy is limited. The torque controlled KUKA joint torque has torque controller. The assembly task. There are several researches the contact perceptual data for the contact state estimation can be various light-weight robot iswas used, whichtoisthe specially designed for feedback controller applied automatic assembly state estimation during position, assemblyforce, taskvision execution. The sensor signals including and so on. sensing joint torque and has torque feedback controller. The perceptual data including for during the contact state force, estimation canand be various light-weight robot iswas used, which specially designed for feedback controller applied toisfeedback the automatic assembly state estimation assembly taskvision execution. The sensor signals position, sostate on. sensing joint torque and has torque controller. The using the FT sensor at the end-effector or joint torque perceptual data for the contact state estimation can be various Debus et al. (2004) approached to estimate the contact controller was applied to feedback the automatic assembly sensor signals including position, force, vision and sostate on. feedback sensing joint torque and has torque controller. The using the FT sensor at the end-effector or joint torque perceptual data for the contact state estimation can be various Debus et al. (2004) approached to estimate the contact feedback controller was applied to the automatic assembly and the compliance joint sensor signals including position, force, vision and soonly on. sensors. between a robot and its environment considering using theThe FTimpedance sensor atcontroller the end-effector or joint torque Debus et al. (2004) approached to estimate the contact feedback controller was applied to the automatic assembly and the compliance joint sensor signals including position, force, vision and contact sostate on. sensors. between asensors robot and its environment considering only using theThe FTimpedance sensor atcontroller the end-effector or joint torque controller have been researched for the more complicated Debus et al. (2004) approached to estimate the contact state kinematic with geometric properties. The andthethemore compliance joint between asensors robot and its environment considering only sensors. usingwith theThe FTimpedance sensor atcontroller the end-effector or joint torque controller have beenofresearched for complicated Debus et al. (2004) approached to estimate the contact state kinematic with geometric properties. The contact sensors. The impedance controller and the compliance joint task these kind sensors. Jasim et al. (2014) suggested between a robotwasandsuccessfully its environment considering only controller have been researched for the more complicated state sequence estimated byThea contact hidden kinematic sensors with geometric properties. sensors. The impedance controller and the compliance joint task with these kind of sensors. Jasim et al. (2014) suggested between a robot and its environment considering only state sequence was successfully estimated by a hidden controller have been researched for the more complicated a strategy for identifying the accurate hole position in forcekinematicmodel sensors with geometric properties. contact Markov in thesuccessfully circle peg-in-hole task.byThe Park et al. task with these kind ofresearched sensors. Jasim et al.more (2014) suggested state sequence was estimated a hidden controller have been for the complicated a strategy for identifying the accurate hole position in forcekinematic sensors geometric properties. Markov model in the circle peg-in-hole Park et FT al. task with these peg-in-hole kind of sensors. Jasimtasks et al.through (2014)employing suggested guided robotic assembly state sequence waswith successfully estimated byThe a contact hidden (2012) additionally used force/torque datatask. obtained by aguided strategy for identifying the accurate hole position in forceMarkov model in the circle peg-in-hole task. Park et FT al. the task with these kind of sensors. Jasimtasks et al.through (2014) suggested robotic peg-in-hole assembly employing state sequence was successfully estimated by a hidden (2012) additionally used force/torque data obtained by a strategy for identifying the accurate hole position intorques. forcewrench vector for the cartesian forces and Markov model in the circle peg-in-hole task. Park et al. sensor which is adopted between the robot and the gripper to guided robotic peg-in-hole assembly tasks through employing (2012) additionally usedcircle force/torque dataand obtained by FT aguided strategy forMaximization-based identifying the accurate hole position intorques. forcethe wrench vector for the cartesian forces andemploying Markov model in the peg-in-hole task. Park et al. sensor which is adopted between the robot the gripper to robotic peg-in-hole assembly tasks through Expectation Gaussian Mixtures Model (2012) additionally used force/torque data obtained by FT improvewhich the performance of the contact state estimation. wrench vector for the cartesian forces andemploying torques. sensor is adopted between the robot and the gripper to the guided robotic peg-in-hole assembly tasks through Expectation Maximization-based Gaussian Mixtures Model (2012) additionally used force/torque data obtained by FT improve the performance of the contact state estimation. the wrench vector for the cartesian forces and torques. is applied to the estimate the contact state and sensor which is adopted between theposition robot anddata the gripper to (EM-GMM) data was analyzed with for each Expectation Maximization-based Gaussian Mixtures Model improvewhich the performance of the contact state estimation. FT the wrench vector forto the cartesian forces and state torques. (EM-GMM) is applied thehole estimate the contact and sensor is adopted between theposition robot and the gripper to good data was analyzed with data for Inoue each Expectation Maximization-based Gaussian Mixtures Model performance of the position identification is improve the performance ofpeg-in-hole the contact state estimation. FT assembly state in the square task. Recently, (EM-GMM) is applied to thehole estimate the contact state and sensor data was analyzed with position data for Inoue each Expectation Maximization-based Gaussian Mixtures Model good performance of the position identification is improve the performance of the contact state estimation. FT assembly state in the square peg-in-hole task. Recently, (EM-GMM) is applied to the estimate the contact state and The KUKA light-weight robot which is one of the sensor data was the analyzed with position data for each shown. (2017) proposed neural network with reinforcement good performance of thethehole position identification is assembly state in the square peg-in-hole task. Recently, Inoue (EM-GMM) is applied to estimate the contact state and shown. The KUKA light-weight robot which is one of the sensor was analyzed with position data each good (2017) proposed the neural network withRecently, reinforcement performance of the position is torque controlled washole alsorobot used which in identification theis experiment. assemblydata inthe the square peg-in-hole task. Inoue learning tostate take optimal action by observing theforsensors shown. The KUKArobot light-weight one of the (2017) proposed the neural network with reinforcement good performance of the hole position identification is torque controlled robot was also used in the experiment. assemblyproposed the square peg-in-hole task. Inoue shown. learning tostate takeinthe optimal action by observing the sensors The KUKA light-weight robot whicha is one mating of the Recently, Takahashi et al. (2016) researched novel (2017) the neural network withRecently, reinforcement torque controlled robot was alsorobot used which in the experiment. learning to take the optimal action by observing the sensors shown. The KUKA light-weight is one of the Recently, Takahashi et al. (2016) researched a novel mating (2017) proposed neuralaction network with reinforcement controlled robot was also used in the experiment. learning to take thethe optimal by observing the sensors torque Recently, Takahashi et al.was (2016) a novel mating controlled robot alsoresearched used in the experiment. learning to take the optimal action by observing the sensors 85 torque Recently, Takahashi et al. (2016) researched a novel mating Copyright © 2018 IFAC Recently, Takahashi (2016) researched a novel mating 2405-8963 © IFAC (International Federation of Automatic Control) by Elsevier Ltd.et Allal. rights reserved. Copyright © 2018, 2018 IFAC 85 Hosting Peer review©under of International Federation of Automatic Copyright 2018 responsibility IFAC 85 Control. Copyright © 2018 IFAC 85 10.1016/j.ifacol.2018.11.522 Copyright © 2018 IFAC 85
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technique based on passive alignment principle (PAP) in order to solve the twin problems of accuracy and deformation. Compliance control of the robot manipulator is also required with a force/torque sensor and the force/torque feedback controller. Tang et al. (2016) also proposed an autonomous alignment method by force/torque measurement before insertion phase. A three-point contact model is built up and the pose misalignment between the peg and hole is estimated by force and geometric analysis. The torque controlled robot with a FT sensor or joint torque sensors was used in the most previous researches for the better performance of the assembly task. However, these methods have some disadvantages such as limited application only for the specially designed torque feedback robot and the instability based on the inaccuracy of the FT sensor feedback.
2. PROPOSED DEVICE 2.1 Concept of the Magic Gripper A new type of the passive compliant device which can measure its deformation is proposed. The proposed device, which is called “Magic Gripper”, is composed of the passive compliance module, the displacement measurement module, the controller module and the gripping module as shown in Fig. 2. The proposed device is designed to be applied into the precision part assembly with narrow tolerance and to compensate the position error of the repetitive tasks. Also, the gripping module can be selected as the proper gripper type according to the workpiece such as Fig. 3.
One of the stable robotic assembly technologies is the application of the passive compliant mechanism with the general position controlled robot. Watson et al. (1978) invented the mechanical device, Remote Center Compliance (RCC), that facilitates automated assembly by preventing peg-like objects from jamming when they are inserted into a hole with some clearance. Because the RCC device has the compliance structure between both plates, it allows to compensate for positioning errors due to machine inaccuracy, vibration or tolerance, thereby lowering contact forces and avoiding part and tool damage. Complex control algorithms are not necessary and stability of assembly task is high. Zhao et al., Joo et al. (1998) and Lee (2005) developed the variable remote center compliance devices to overcome the disadvantage of the fixed stiffness and the fixed location of compliant center and to expand the various assembly tasks without additional setup cost. However, the teaching process for the assembly of complex parts with RCC devices is not simple, the failure of the assembly procedure cannot be recognized and the automatic correction of the assembly strategy cannot be possible, because there is no sensor and no feedback of the deformation of the device. Therefore, once the assembly trajectory is fixed in the teaching stage, it is difficult to compensate the position error in the repetitive playback stage.
Fig. 2. Composition of the proposed device
Fig. 3. Gripping module according to the workpiece Several compliant bars which are made of rubber composite and elastic spring are installed between the upper plate and the lower plate such as the remote center compliance device. Also, it has the displacement measurement system which is composed of the stewart platform mechanism and LVDT
Fig. 1. A commercial remote center compliance
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(linear variable differential transformer) sensors for each leg of the stewart platform. Therefore, it can calculate the relative position and the relative orientation of both plates from the measured displacement of each leg.
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A compliance bar is classified into three parts as shown in Fig. 6. A helical spring which is made of aluminium is in the middle of the compliance bar, rubber composite is attached outside of the helical spring and two aluminium supports which can be connected to the plates of the device at both ends. The characteristic of the compliance bar is various according to the shape of the helical spring and the material property of the rubber composite. Therefore, FEM analysis, tension-compression tests and some restoration experiments are carried out to optimize compliance and restoration force. Fig. 7 and Fig. 8 show the examples of the analysis results and the experimental results for the measurement of compliance.
2.2 Passive Compliance Module The passive compliance module is composed of the upper plate, the lower plate and some compliance bars between both plates. The upper cover and the lower cover are attached to each outside of the plates for the mechanical interface of the other module of the device as shown in Fig. 4.
Fig. 4. Composition of the passive compliance module Fig. 7. FEM analysis of a compliance bar
Compliance bars have to be designed to make the required compliance for all directions as shown in Fig. 5 and to have sufficient restoration force for each direction.
Fig. 8. Experiment of the compliance bar
Fig. 5. Each direction of the compliance
The stiffness of the compliance bar is designed to be from about 30kN/m to about 240kN/m according to the material. Although the displacement measurement module is added in the passive compliance module and the compliance device can compensate non-restoring error, the repeatability of itself is also important for the reliability of the device. Fig. 9 shows the restoration experiment of the compliance bar. The measured repeatability is below about 46 um and it is enough to be applied to automatic assembly. Additionally, the allowable displacement is measured for the lateral direction, the torsion direction and the cocking direction as shown in Fig. 10. The allowable displacement is measured as about 2 mm, 5 degree, 1 degree for the lateral direction, the torsion direction and the cocking direction, respectively.
Fig. 6. Composition of a compliance bar
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Fig. 11. Composition of the displace measurement module
Fig. 9. Experiment for restoration force
Fig. 12. Stewart platform with displacement sensors Each leg of the stewart platform mechanism includes a LVDT (linear variable differential transformer) sensor and the length of six legs can be measured. Then, six DOF pose which includes three positions and three orientations can be calculated from the measured lengths using a kinematic equation of stewart platform as shown in Fig. 13. (a) Experiment for lateral and torsion
Fig. 13. General kinematics of stewart platform
(b) Experimental for cocking
Six DOF pose information can be used for the compensation of the errors which happened in previous assembly task or in the teaching process. After each LVDT sensor is calibrated, accuracy of the measurement displacement is below about 30um and the calculated position accuracy is below about 60um.
Fig. 10. Experiment for allowable displacement measurement 2.3 Displacement measurement module As mentioned in the previous section, a set of displacement measurement sensors is implemented as the displacement measurement module to measure the position and the orientation between the upper plate and the lower plate. The stewart platform mechanism which is a kind of parallel kinematic robot is selected to measure six DOF pose between both plates. Fig. 11 and Fig. 12 show the displacement measurement module with LVDT sensors.
3. ASSEMBLY STRATEGY 3.1 Assembly task The proposed passive compliance device with the displacement measurement module is applied to the square peg-in-hole assembly task. The square peg and the square
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hole are represented as Fig. 14 and the tolerance of the assembly task is about 200um.
(b) Teaching phase
Fig. 14. Square peg-in-hole assembly task 3.2 Assembly strategy (c) Playback phase
Fig. 16. Assembly strategy The trajectory compensation is carried out by using (2) and (3) and the generated trajectory is used in the playback phase.
Fig. 15. Sequence of the assembly strategy A new assembly strategy using the passive compliant device with displacement measurement system is proposed. Assembly task is classified into two stages including the teaching phase and the playback phase. Its sequence includes approach to the workpiece, manual guided assembly, calculation of device displacement, generation/compensation of new trajectory and playback with assembly strategy. Assembly teaching procedure can be easily carried out and the generated trajectory can make the playback phase of the assembly task to be successful. Fig. 15 and Fig. 16 show the assembly strategy in detail.
4. EXPERIMENT 4.1 Experimental setup The proposed device is attached to the tip of the robot manipulator and the experimental setup for peg-in-hole
(a) Block diagram with the proposed assembly strategy
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assembly is built as Fig. 17. The square peg-in-hole task is carried out using the proposed assembly strategy which is mentioned in the previous section. The first phase is the teaching process with both a teach pendant and manual guidance and the second phase is the playback process with the compensated trajectory based on the calculation of the error.
generation/compensation of new trajectory and playback with assembly strategy. The proposed assembly method is applied into the square peg in hole task which has about 200um tolerance. Assembly teaching procedure is easily carried out and the generated trajectory can make the playback phase of the assembly task to be successful. The proposed device and the proposed assembly strategy are proved to be very useful for automatic assembly of the precision parts. In the future, repeatability of the proposed device and accuracy of the displacement measurement system will be improved for the more precise assembly task. REFERENCES Debus, T., Dupont, Pierre E., and Howe, Robert D. (2004). Contact State Estimation Using Multiple Model Estimation and Hidden Markov Models. International Journal of Robotic Research, 23(4-5), 399-413 Park, D., Park, C., Do, H., Choi, T., and Kyung, J. (2012). Contact state analysis using FT sensor in the square pegin hole. 2012 International Conference on Electronics, Information and Communication, 394-395 Inoue, T., Magistris, G.D., Munawar, A., Yokoya, T., and Tachibana, R. (2017). Deep reinforcement learning for high precision assembly tasks. IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 819-825 Stemmer, A., Schreiber, G., Arbter, K., and Albu-Schaeffer, A. (2006). Robust Assembly of Complex Shaped Planar Parts Using Vision and Force. IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Heidelberg, Germany, 493-500 Jasim, I.F., Plapper, P.W., and Voos, H. (2014). Position Identification in Force-Guided Robotic Peg-in-Hole Assembly Tasks, Procedia CIRP, 23, 217-222 Takahashi, J., Fukukawa, T., and Fukuda, T. (2016). Passive Alignment Principle for Robotic Assembly Between a Ring and a Shaft With Extremely Narrow Clearance. IEEE/ASME Transactions on Mechatronics, 21(1), 196204 Tang, T., Lin, H., Zhao, Y., Chen, W., and Tomizuka, M. (2016). Autonomous alignment of peg and hole by force/torque measurement for robotic assembly. 2016 IEEE International Conference on Automation Science and Engineering(CASE), 162-167 Watson, P.C. (1978). Remote center compliance system, U.S. Patent 4,098,001 Zhao, F, and Wu P.S.Y (1998). VRCC : a variable remote center compliance device. Mechatronics, 8(6), 657-672 Joo, S., and Miyaziki, F. (1998). Development of variable RCC and its application. IEEE/RSJ Conf. on Intelligent Robots and Systems, 1326-1332 Lee, S. (2005). Development of a new variable remote center compliance (VRCC) with modified elastomer shear pad (ESP) for robot assembly. IEEE Transactions on Automation Science and Engineering, 2, 193-197
Fig. 17. Experimental setup for automatic assembly 4.2 Experimental result The proposed device and the proposed assembly method are applied into the square peg-in-hole task. Assembly teaching procedure is easily carried out with some errors and the playback assembly is successful without any additional behaviour.
Fig. 18. Experimental result of teaching and playback 5. CONCLUSIONS In the paper, we proposed a new type of the passive compliant device which can measure its deformation. The proposed device, which is called “Magic Gripper”, is composed of the passive compliance module, the gripping module, the displacement measurement module and the controller module. Also, a new assembly strategy using the passive compliant device with displacement measurement system is proposed. Assembly task is classified into two stages including the teaching phase and the playback phase. Its sequence includes approach to the workpiece, manual guided assembly, calculation of device displacement,
ACKNOWLODGEMENT This research is funded by the R&D program of the MKE, Korea government. 90
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IFAC PapersOnLine 85–90 Passive compliant module with 51-22 the (2018) displacement measurement sensor Passive compliant module with the displacement measurement sensor Passive module with measurement and its application fordisplacement automatic assembly Passive compliant compliant module with the the measurement sensor sensor and its application fordisplacement automatic assembly Passive compliant module with the displacement measurement sensor and its application for automatic assembly and its application forTaeyong automatic assembly Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Choi*. Jongwoo Park* and Byungin Kim* and its application forTaeyong automatic assembly Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Choi*. Jongwoo Park* and Byungin Kim*
Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Taeyong Choi*. Jongwoo Park* and Byungin Kim* Dong Il Park1*. Hwisu Kim*. Chanhun Park*. Taeyong Choi*. Jongwoo Park* and Byungin Kim* Dong Il Park1*. HwisuofKim*. Chanhun Park*. Taeyong Jongwoo Park*&and Byungin Kim* * Department Robotics and Mechatronics, KoreaChoi*. Institute of Machinery Materials * Department of Robotics and +82-42-868-7984; Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: e-mail:[email protected]) * Department of Robotics and +82-42-868-7984; Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: e-mail:[email protected]) * Department of Robotics and Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: +82-42-868-7984; e-mail:[email protected]) * Department of Robotics and +82-42-868-7984; Mechatronics, Korea Institute of Machinery & Materials Daejeon, Korea (Tel: e-mail:[email protected]) Korea (Tel: +82-42-868-7984; e-mail:[email protected]) Abstract: Robot Daejeon, manipulators have been applied in the various automated manufacturing for handling, Abstract: Robot manipulators have been deburring, applied in simple the various automated for handling, transferring, welding, polishing, painting, assembly and so manufacturing on. Robotic assembly of the Abstract: Robot manipulators have been deburring, applied in simple the various automated manufacturing for handling, transferring, welding, polishing, painting, assembly and so on. Robotic assembly of the Abstract: Robot manipulators havethebeen applied inthethe various automated manufacturing for handling, precision parts is difficult because accuracy of robot manipulator is not enough and the teaching transferring, welding, polishing, painting, deburring, simple assembly and is sonot on. enough Roboticand assembly of the Abstract: Robot have applied the various automated manufacturing precision is manipulators difficult because thebeen accuracy ofinthe robot manipulator the teaching transferring, welding, polishing, painting, deburring, simple assembly and soassembly on. Robotic assembly of the procedureparts is complex. There have been various technologies about robotic such asfor thehandling, position precision parts is difficult because the accuracy of the robot manipulator is not enough and the teaching transferring, polishing, painting, deburring, simple andwith soassembly on. Robotic assembly of the procedure is welding, complex. There have been various technologies about robotic such as the the teaching position precision parts isstrategy, difficult because thetorque accuracy of the robotassembly manipulator is not enough and based assembly the active feedback control algorithm FT sensor or joint torque procedure is complex. There have been various technologies about robotic assembly such as the the teaching position precision parts is difficult because the accuracy of the robot manipulator is not enough and based assembly strategy, the active torque feedback control algorithm with FT sensor or joint torque procedure is complex. There have been various technologies about robotic assembly such as the position sensorsassembly and the remote center compliance which gives the passive compliance to the end-effector. In the based strategy, thehave active torque feedback algorithm with FT sensor or torque procedure isthe complex. There been various technologies about robotic assembly such as joint the position sensors andproposed remote center compliance which givescontrol thedevice passive compliance to the end-effector. InThe the based assembly strategy, the active torque feedback control algorithm with FT sensor or joint torque paper, we a new type of the passive compliant which can measure its deformation. sensorsassembly andproposed the remote center compliance which givescontrol thedevice passive compliance to the end-effector. InThe the based strategy, the active torque feedback algorithm with FT sensor or joint torque paper, we a new type of the passive compliant which can measure its deformation. sensors and the remote center compliance which gives the passive compliance to the end-effector. In the proposed device, which is type calledof“Magic Gripper”, is composed of thecan passive compliance module,The paper, we proposed a new the passive compliant device which measure itsend-effector. deformation. sensors and the remote center compliance which gives the passive compliance to the In proposed device, which is called “Magic Gripper”, is composed of the passive compliance module, the paper, we module, proposedthe a new type of the measurement passive compliant device which can measure its deformation. The gripping displacement module and the controller module. Also, a new proposed device, which is type calledof“Magic Gripper”, is composed of thecontroller passive compliance module, the paper, we module, proposed a new the measurement passive compliant device measure its deformation. The gripping the displacement module and the module. Also, a new proposed device, which isthe called “Magic Gripper”, is composed of thecan passive compliance module, the assembly strategy using passive compliant device with thewhich displacement measurement system is gripping module, the displacement measurement module and the controller module. Also, a new proposed device, which isdevice called “Magic Gripper”, is composed thecontroller passive compliance module, the assembly strategy usingdisplacement the passive compliant device with and the of displacement measurement system is gripping module, the measurement module the module. Also, a new proposed. The proposed and the proposed assembly strategy are proved to be very useful for assembly strategy usingdisplacement the passive compliant device with and the the displacement system is gripping the measurement module controller module. Also, a new proposed. The proposed andparts. the proposed assembly are provedmeasurement to be very useful for assembly strategy using the passive compliant device with strategy the displacement measurement system is automaticmodule, assembly of thedevice precision proposed. The proposed device and the proposed assembly strategy are proved to be very useful for assembly using the passive compliant device with strategy the displacement systemfor is automatic assembly of thedevice precision proposed. strategy The proposed andparts. the proposed assembly are provedmeasurement to be very useful automatic assembly of thedevice precision © 2018, IFAC (International Federation of Automatic by Elsevier Ltd. proposed. The proposed andparts. the proposed assembly strategy are proved toAllberights veryreserved. useful for Keywords: Robotic assembly, Automatic assembly,Control) RemoteHosting center compliance, Magic gripper, Passive automatic assembly of the precision parts. Keywords: Robotic of assembly, Automatic automatic the precision parts. assembly, Remote center compliance, Magic gripper, Passive complianceassembly Keywords: assembly, Automatic assembly, Remote center compliance, Magic gripper, Passive compliance Robotic Keywords: Robotic assembly, Automatic assembly, Remote center compliance, Magic gripper, Passive compliance Robotic assembly, Automatic assembly, Remote center compliance, Magic gripper, Passive Keywords: compliance compliance of a robot to estimate the system state and to increase the 1. INTRODUCTION of a robot to the task. system state kinds and to ofincrease the robustness of estimate assembly These assembly 1. INTRODUCTION of a robot to estimate the task. system state kinds and to ofincrease the robustness of assembly These assembly a robot to estimate the system state andsystematical to increase and the INTRODUCTION algorithms make the assembly state to be Robot manipulators1. have been applied in the various of robustness of assembly task. These kinds of assembly 1. INTRODUCTION of a robot to estimate the task. system state andsuccess to ofincrease the make the assembly state tothe be systematical and Robot manipulators have been applied in the welding, various algorithms robustness ofand assembly These kinds assembly hierarchical obviously increase rates of 1. INTRODUCTION automated manufacturing for handling, transferring, make the assembly state tothe be systematical and Robot manipulators have been applied in the welding, various algorithms robustness of assembly task. These kinds of assembly hierarchical and obviously increase success rates of automated manufacturing for handling, transferring, algorithms make the assembly state to be systematical and assembly task by classifying the assembly states Robot manipulators have been applied in the various polishing, painting, deburring, simple assembly and so on. hierarchical and by obviously increase the success ratesand of automated manufacturing for been handling, transferring, welding, algorithms make the assembly state to be systematical assembly task classifying the assembly states Robot manipulators have applied in the various polishing, painting, deburring, simple assembly and so on. hierarchical and obviously increase the success rates of monitoring the by current assemblythestates. However, these automated manufacturing forcan handling, transferring, welding, These kindspainting, of applications be implemented by the robot assembly task classifying assembly states and polishing, deburring, simple assembly and so on. hierarchical and obviously increase the success rates of monitoring the current assembly states. However, these automated manufacturing for handling, transferring, welding, These kinds of applications can be implemented by the robot assembly task by classifying the assembly states and algorithms cannot reduce the effort and time for the teaching polishing, painting, deburring, simple assembly and sotask. on. monitoring the current assembly states. However, these programming orapplications robot teaching for the simple repetitive These kinds of can be implemented by the robot assembly task by classifying the assembly states and algorithms cannot reduce the effort and time for the teaching polishing, deburring, simple assembly and sorobot on. programming robot teaching thethe simple repetitive task. the current assemblythestates. However, process andcannot cannot compensate position ofthese the These kindspainting, oforapplications can for beofimplemented by the However, automatic precision parts is monitoring algorithms reduce the effortthe and time However, for error the teaching programming orapplications robot assembly teaching for thethe simple repetitive task. monitoring the current assembly states. process andcannot cannot compensate position error ofthese the These kinds of can be implemented by the robot However, automatic assembly of precision parts is algorithms reduce the effort and time for the teaching taught trajectory in the repetitive playback phase. programming or robot teaching for the simple repetitive task. difficult because of theassembly accuracy ofof the robot manipulator and process andcannot cannot compensate the position error of the However, automatic precision parts is algorithms reduce the effort and time for the teaching taught trajectory in the repetitive playback phase. programming or robot teaching for the simple repetitive task. difficult because of theprocedure. accuracy ofof the robot manipulator and cannot compensate the position error of the However, automatic assembly precision partsand is process the complex teaching taught trajectory in(2006) the repetitive phase. difficult because of theprocedure. accuracy ofofthethe robot manipulator process and cannot the fusion position of and the Stemmer et al. studied playback the oferror vision However, automatic precision partsand is taught the complex teaching trajectory in thecompensate repetitive playback phase. difficult because of theassembly accuracy of the robot manipulator and Stemmer et al. (2006) studied the fusion of vision and the complex teaching procedure. taught trajectory in the repetitive playback phase. force/torque information for robotic assembly tasks. The difficult because of the accuracy of the robot manipulator and Various assembly strategies with the assembly state Stemmer et information al. (2006) studied the fusion of vision and the complex teaching procedure. for robotic assembly tasks. The Various assembly strategies the with assembly state force/torque Stemmer et al. the afusion vision and vision system was(2006) used tostudied determine global of initial position the complex teaching procedure. with estimation, active compliance control the force force/torque information for robotic assembly tasks. The Various assembly strategies with the assembly state Stemmer et al. (2006) studied the fusion of vision and vision system was used to determine a global initial position estimation, active compliance control with the force force/torque information for robotic assembly tasks. The of was the used objects. However,a global the torque feedback Various assembly strategies with the assembly state estimation controlled robot and compliance passive compliant device such as force RCC vision system to for determine initial position estimation, active control with the force/torque information robotic assembly tasks. The estimation of the objects. However, the torque feedback Various strategies with assembly state controlled robot and compliance passive compliant device such RCC system was used to be determine global initial position control algorithm had to applieda because vision based estimation, active control with theasofforce have beenassembly researched to improve the the performance the vision estimation of was the used objects. However, the torque feedback controlled robot and compliance passive compliant device such asofforce RCC vision system to be determine a because global initial position control algorithm had to applied vision based estimation, active control with the have been researched to improve the performance the estimation of the objects. However, the torque feedback position accuracy is limited. The torque controlled controlled robotThere and passive compliant device such ascontact RCC control algorithm had to be applied because visionKUKA assembly task. are several researches about the based have been researched to improve the performance of the estimation of the objects. However, the torque feedback position accuracy is limited. The torque controlled KUKA controlled robot and passive compliant device such assembly task. There aretoseveral researches about theascontact algorithm had to bewhich applied because vision based light-weight robot is is limited. used, is specially designed for have been researched improve thetask performance ofRCC the control state estimation during assembly execution. The position accuracy The torque controlled KUKA assembly task. There aretoseveral researches about the contact control algorithm had tohas bewhich applied because vision based light-weight robot isand used, isfeedback specially designed for have been researched improve the performance of the state estimation during assembly task execution. The position accuracy is limited. The torque controlled KUKA sensing joint torque torque controller. The assembly task. There are several researches about the contact perceptual data for during the contact state estimation can be various light-weight robot isand used, which isfeedback specially designed for state estimation assembly task about execution. The sensing position accuracy is limited. The torque controlled KUKA joint torque has torque controller. The assembly task. There are several researches the contact perceptual data for the contact state estimation can be various light-weight robot iswas used, whichtoisthe specially designed for feedback controller applied automatic assembly state estimation during position, assemblyforce, taskvision execution. The sensor signals including and so on. sensing joint torque and has torque feedback controller. The perceptual data including for during the contact state force, estimation canand be various light-weight robot iswas used, which specially designed for feedback controller applied toisfeedback the automatic assembly state estimation assembly taskvision execution. The sensor signals position, sostate on. sensing joint torque and has torque controller. The using the FT sensor at the end-effector or joint torque perceptual data for the contact state estimation can be various Debus et al. (2004) approached to estimate the contact controller was applied to feedback the automatic assembly sensor signals including position, force, vision and sostate on. feedback sensing joint torque and has torque controller. The using the FT sensor at the end-effector or joint torque perceptual data for the contact state estimation can be various Debus et al. (2004) approached to estimate the contact feedback controller was applied to the automatic assembly and the compliance joint sensor signals including position, force, vision and soonly on. sensors. between a robot and its environment considering using theThe FTimpedance sensor atcontroller the end-effector or joint torque Debus et al. (2004) approached to estimate the contact feedback controller was applied to the automatic assembly and the compliance joint sensor signals including position, force, vision and contact sostate on. sensors. between asensors robot and its environment considering only using theThe FTimpedance sensor atcontroller the end-effector or joint torque controller have been researched for the more complicated Debus et al. (2004) approached to estimate the contact state kinematic with geometric properties. The andthethemore compliance joint between asensors robot and its environment considering only sensors. usingwith theThe FTimpedance sensor atcontroller the end-effector or joint torque controller have beenofresearched for complicated Debus et al. (2004) approached to estimate the contact state kinematic with geometric properties. The contact sensors. The impedance controller and the compliance joint task these kind sensors. Jasim et al. (2014) suggested between a robotwasandsuccessfully its environment considering only controller have been researched for the more complicated state sequence estimated byThea contact hidden kinematic sensors with geometric properties. sensors. The impedance controller and the compliance joint task with these kind of sensors. Jasim et al. (2014) suggested between a robot and its environment considering only state sequence was successfully estimated by a hidden controller have been researched for the more complicated a strategy for identifying the accurate hole position in forcekinematicmodel sensors with geometric properties. contact Markov in thesuccessfully circle peg-in-hole task.byThe Park et al. task with these kind ofresearched sensors. Jasim et al.more (2014) suggested state sequence was estimated a hidden controller have been for the complicated a strategy for identifying the accurate hole position in forcekinematic sensors geometric properties. Markov model in the circle peg-in-hole Park et FT al. task with these peg-in-hole kind of sensors. Jasimtasks et al.through (2014)employing suggested guided robotic assembly state sequence waswith successfully estimated byThe a contact hidden (2012) additionally used force/torque datatask. obtained by aguided strategy for identifying the accurate hole position in forceMarkov model in the circle peg-in-hole task. Park et FT al. the task with these kind of sensors. Jasimtasks et al.through (2014) suggested robotic peg-in-hole assembly employing state sequence was successfully estimated by a hidden (2012) additionally used force/torque data obtained by a strategy for identifying the accurate hole position intorques. forcewrench vector for the cartesian forces and Markov model in the circle peg-in-hole task. Park et al. sensor which is adopted between the robot and the gripper to guided robotic peg-in-hole assembly tasks through employing (2012) additionally usedcircle force/torque dataand obtained by FT aguided strategy forMaximization-based identifying the accurate hole position intorques. forcethe wrench vector for the cartesian forces andemploying Markov model in the peg-in-hole task. Park et al. sensor which is adopted between the robot the gripper to robotic peg-in-hole assembly tasks through Expectation Gaussian Mixtures Model (2012) additionally used force/torque data obtained by FT improvewhich the performance of the contact state estimation. wrench vector for the cartesian forces andemploying torques. sensor is adopted between the robot and the gripper to the guided robotic peg-in-hole assembly tasks through Expectation Maximization-based Gaussian Mixtures Model (2012) additionally used force/torque data obtained by FT improve the performance of the contact state estimation. the wrench vector for the cartesian forces and torques. is applied to the estimate the contact state and sensor which is adopted between theposition robot anddata the gripper to (EM-GMM) data was analyzed with for each Expectation Maximization-based Gaussian Mixtures Model improvewhich the performance of the contact state estimation. FT the wrench vector forto the cartesian forces and state torques. (EM-GMM) is applied thehole estimate the contact and sensor is adopted between theposition robot and the gripper to good data was analyzed with data for Inoue each Expectation Maximization-based Gaussian Mixtures Model performance of the position identification is improve the performance ofpeg-in-hole the contact state estimation. FT assembly state in the square task. Recently, (EM-GMM) is applied to thehole estimate the contact state and sensor data was analyzed with position data for Inoue each Expectation Maximization-based Gaussian Mixtures Model good performance of the position identification is improve the performance of the contact state estimation. FT assembly state in the square peg-in-hole task. Recently, (EM-GMM) is applied to the estimate the contact state and The KUKA light-weight robot which is one of the sensor data was the analyzed with position data for each shown. (2017) proposed neural network with reinforcement good performance of thethehole position identification is assembly state in the square peg-in-hole task. Recently, Inoue (EM-GMM) is applied to estimate the contact state and shown. The KUKA light-weight robot which is one of the sensor was analyzed with position data each good (2017) proposed the neural network withRecently, reinforcement performance of the position is torque controlled washole alsorobot used which in identification theis experiment. assemblydata inthe the square peg-in-hole task. Inoue learning tostate take optimal action by observing theforsensors shown. The KUKArobot light-weight one of the (2017) proposed the neural network with reinforcement good performance of the hole position identification is torque controlled robot was also used in the experiment. assemblyproposed the square peg-in-hole task. Inoue shown. learning tostate takeinthe optimal action by observing the sensors The KUKA light-weight robot whicha is one mating of the Recently, Takahashi et al. (2016) researched novel (2017) the neural network withRecently, reinforcement torque controlled robot was alsorobot used which in the experiment. learning to take the optimal action by observing the sensors shown. The KUKA light-weight is one of the Recently, Takahashi et al. (2016) researched a novel mating (2017) proposed neuralaction network with reinforcement controlled robot was also used in the experiment. learning to take thethe optimal by observing the sensors torque Recently, Takahashi et al.was (2016) a novel mating controlled robot alsoresearched used in the experiment. learning to take the optimal action by observing the sensors 85 torque Recently, Takahashi et al. (2016) researched a novel mating Copyright © 2018 IFAC Recently, Takahashi (2016) researched a novel mating 2405-8963 © IFAC (International Federation of Automatic Control) by Elsevier Ltd.et Allal. rights reserved. Copyright © 2018, 2018 IFAC 85 Hosting Peer review©under of International Federation of Automatic Copyright 2018 responsibility IFAC 85 Control. Copyright © 2018 IFAC 85 10.1016/j.ifacol.2018.11.522 Copyright © 2018 IFAC 85
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technique based on passive alignment principle (PAP) in order to solve the twin problems of accuracy and deformation. Compliance control of the robot manipulator is also required with a force/torque sensor and the force/torque feedback controller. Tang et al. (2016) also proposed an autonomous alignment method by force/torque measurement before insertion phase. A three-point contact model is built up and the pose misalignment between the peg and hole is estimated by force and geometric analysis. The torque controlled robot with a FT sensor or joint torque sensors was used in the most previous researches for the better performance of the assembly task. However, these methods have some disadvantages such as limited application only for the specially designed torque feedback robot and the instability based on the inaccuracy of the FT sensor feedback.
2. PROPOSED DEVICE 2.1 Concept of the Magic Gripper A new type of the passive compliant device which can measure its deformation is proposed. The proposed device, which is called “Magic Gripper”, is composed of the passive compliance module, the displacement measurement module, the controller module and the gripping module as shown in Fig. 2. The proposed device is designed to be applied into the precision part assembly with narrow tolerance and to compensate the position error of the repetitive tasks. Also, the gripping module can be selected as the proper gripper type according to the workpiece such as Fig. 3.
One of the stable robotic assembly technologies is the application of the passive compliant mechanism with the general position controlled robot. Watson et al. (1978) invented the mechanical device, Remote Center Compliance (RCC), that facilitates automated assembly by preventing peg-like objects from jamming when they are inserted into a hole with some clearance. Because the RCC device has the compliance structure between both plates, it allows to compensate for positioning errors due to machine inaccuracy, vibration or tolerance, thereby lowering contact forces and avoiding part and tool damage. Complex control algorithms are not necessary and stability of assembly task is high. Zhao et al., Joo et al. (1998) and Lee (2005) developed the variable remote center compliance devices to overcome the disadvantage of the fixed stiffness and the fixed location of compliant center and to expand the various assembly tasks without additional setup cost. However, the teaching process for the assembly of complex parts with RCC devices is not simple, the failure of the assembly procedure cannot be recognized and the automatic correction of the assembly strategy cannot be possible, because there is no sensor and no feedback of the deformation of the device. Therefore, once the assembly trajectory is fixed in the teaching stage, it is difficult to compensate the position error in the repetitive playback stage.
Fig. 2. Composition of the proposed device
Fig. 3. Gripping module according to the workpiece Several compliant bars which are made of rubber composite and elastic spring are installed between the upper plate and the lower plate such as the remote center compliance device. Also, it has the displacement measurement system which is composed of the stewart platform mechanism and LVDT
Fig. 1. A commercial remote center compliance
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(linear variable differential transformer) sensors for each leg of the stewart platform. Therefore, it can calculate the relative position and the relative orientation of both plates from the measured displacement of each leg.
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A compliance bar is classified into three parts as shown in Fig. 6. A helical spring which is made of aluminium is in the middle of the compliance bar, rubber composite is attached outside of the helical spring and two aluminium supports which can be connected to the plates of the device at both ends. The characteristic of the compliance bar is various according to the shape of the helical spring and the material property of the rubber composite. Therefore, FEM analysis, tension-compression tests and some restoration experiments are carried out to optimize compliance and restoration force. Fig. 7 and Fig. 8 show the examples of the analysis results and the experimental results for the measurement of compliance.
2.2 Passive Compliance Module The passive compliance module is composed of the upper plate, the lower plate and some compliance bars between both plates. The upper cover and the lower cover are attached to each outside of the plates for the mechanical interface of the other module of the device as shown in Fig. 4.
Fig. 4. Composition of the passive compliance module Fig. 7. FEM analysis of a compliance bar
Compliance bars have to be designed to make the required compliance for all directions as shown in Fig. 5 and to have sufficient restoration force for each direction.
Fig. 8. Experiment of the compliance bar
Fig. 5. Each direction of the compliance
The stiffness of the compliance bar is designed to be from about 30kN/m to about 240kN/m according to the material. Although the displacement measurement module is added in the passive compliance module and the compliance device can compensate non-restoring error, the repeatability of itself is also important for the reliability of the device. Fig. 9 shows the restoration experiment of the compliance bar. The measured repeatability is below about 46 um and it is enough to be applied to automatic assembly. Additionally, the allowable displacement is measured for the lateral direction, the torsion direction and the cocking direction as shown in Fig. 10. The allowable displacement is measured as about 2 mm, 5 degree, 1 degree for the lateral direction, the torsion direction and the cocking direction, respectively.
Fig. 6. Composition of a compliance bar
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Fig. 11. Composition of the displace measurement module
Fig. 9. Experiment for restoration force
Fig. 12. Stewart platform with displacement sensors Each leg of the stewart platform mechanism includes a LVDT (linear variable differential transformer) sensor and the length of six legs can be measured. Then, six DOF pose which includes three positions and three orientations can be calculated from the measured lengths using a kinematic equation of stewart platform as shown in Fig. 13. (a) Experiment for lateral and torsion
Fig. 13. General kinematics of stewart platform
(b) Experimental for cocking
Six DOF pose information can be used for the compensation of the errors which happened in previous assembly task or in the teaching process. After each LVDT sensor is calibrated, accuracy of the measurement displacement is below about 30um and the calculated position accuracy is below about 60um.
Fig. 10. Experiment for allowable displacement measurement 2.3 Displacement measurement module As mentioned in the previous section, a set of displacement measurement sensors is implemented as the displacement measurement module to measure the position and the orientation between the upper plate and the lower plate. The stewart platform mechanism which is a kind of parallel kinematic robot is selected to measure six DOF pose between both plates. Fig. 11 and Fig. 12 show the displacement measurement module with LVDT sensors.
3. ASSEMBLY STRATEGY 3.1 Assembly task The proposed passive compliance device with the displacement measurement module is applied to the square peg-in-hole assembly task. The square peg and the square
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hole are represented as Fig. 14 and the tolerance of the assembly task is about 200um.
(b) Teaching phase
Fig. 14. Square peg-in-hole assembly task 3.2 Assembly strategy (c) Playback phase
Fig. 16. Assembly strategy The trajectory compensation is carried out by using (2) and (3) and the generated trajectory is used in the playback phase.
Fig. 15. Sequence of the assembly strategy A new assembly strategy using the passive compliant device with displacement measurement system is proposed. Assembly task is classified into two stages including the teaching phase and the playback phase. Its sequence includes approach to the workpiece, manual guided assembly, calculation of device displacement, generation/compensation of new trajectory and playback with assembly strategy. Assembly teaching procedure can be easily carried out and the generated trajectory can make the playback phase of the assembly task to be successful. Fig. 15 and Fig. 16 show the assembly strategy in detail.
4. EXPERIMENT 4.1 Experimental setup The proposed device is attached to the tip of the robot manipulator and the experimental setup for peg-in-hole
(a) Block diagram with the proposed assembly strategy
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assembly is built as Fig. 17. The square peg-in-hole task is carried out using the proposed assembly strategy which is mentioned in the previous section. The first phase is the teaching process with both a teach pendant and manual guidance and the second phase is the playback process with the compensated trajectory based on the calculation of the error.
generation/compensation of new trajectory and playback with assembly strategy. The proposed assembly method is applied into the square peg in hole task which has about 200um tolerance. Assembly teaching procedure is easily carried out and the generated trajectory can make the playback phase of the assembly task to be successful. The proposed device and the proposed assembly strategy are proved to be very useful for automatic assembly of the precision parts. In the future, repeatability of the proposed device and accuracy of the displacement measurement system will be improved for the more precise assembly task. REFERENCES Debus, T., Dupont, Pierre E., and Howe, Robert D. (2004). Contact State Estimation Using Multiple Model Estimation and Hidden Markov Models. International Journal of Robotic Research, 23(4-5), 399-413 Park, D., Park, C., Do, H., Choi, T., and Kyung, J. (2012). Contact state analysis using FT sensor in the square pegin hole. 2012 International Conference on Electronics, Information and Communication, 394-395 Inoue, T., Magistris, G.D., Munawar, A., Yokoya, T., and Tachibana, R. (2017). Deep reinforcement learning for high precision assembly tasks. IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 819-825 Stemmer, A., Schreiber, G., Arbter, K., and Albu-Schaeffer, A. (2006). Robust Assembly of Complex Shaped Planar Parts Using Vision and Force. IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Heidelberg, Germany, 493-500 Jasim, I.F., Plapper, P.W., and Voos, H. (2014). Position Identification in Force-Guided Robotic Peg-in-Hole Assembly Tasks, Procedia CIRP, 23, 217-222 Takahashi, J., Fukukawa, T., and Fukuda, T. (2016). Passive Alignment Principle for Robotic Assembly Between a Ring and a Shaft With Extremely Narrow Clearance. IEEE/ASME Transactions on Mechatronics, 21(1), 196204 Tang, T., Lin, H., Zhao, Y., Chen, W., and Tomizuka, M. (2016). Autonomous alignment of peg and hole by force/torque measurement for robotic assembly. 2016 IEEE International Conference on Automation Science and Engineering(CASE), 162-167 Watson, P.C. (1978). Remote center compliance system, U.S. Patent 4,098,001 Zhao, F, and Wu P.S.Y (1998). VRCC : a variable remote center compliance device. Mechatronics, 8(6), 657-672 Joo, S., and Miyaziki, F. (1998). Development of variable RCC and its application. IEEE/RSJ Conf. on Intelligent Robots and Systems, 1326-1332 Lee, S. (2005). Development of a new variable remote center compliance (VRCC) with modified elastomer shear pad (ESP) for robot assembly. IEEE Transactions on Automation Science and Engineering, 2, 193-197
Fig. 17. Experimental setup for automatic assembly 4.2 Experimental result The proposed device and the proposed assembly method are applied into the square peg-in-hole task. Assembly teaching procedure is easily carried out with some errors and the playback assembly is successful without any additional behaviour.
Fig. 18. Experimental result of teaching and playback 5. CONCLUSIONS In the paper, we proposed a new type of the passive compliant device which can measure its deformation. The proposed device, which is called “Magic Gripper”, is composed of the passive compliance module, the gripping module, the displacement measurement module and the controller module. Also, a new assembly strategy using the passive compliant device with displacement measurement system is proposed. Assembly task is classified into two stages including the teaching phase and the playback phase. Its sequence includes approach to the workpiece, manual guided assembly, calculation of device displacement,
ACKNOWLODGEMENT This research is funded by the R&D program of the MKE, Korea government. 90