Fuzzy Tools for Telepresence with a Mobile Robot

Copyright © IFAC Human-Oriented Design of Advanced Robotics Systems, Vienna, Austria, 1995

FUZZY TOOLS FOR TELEPRESENCE WITH A MOBILE ROBOT

J.-G. Fontaine, N. Cislo, A. Kheddar Laboratoire de Robotique de Paris Universite Pierre et Afarie Curie / Universite Versailles-St Quentin URA CNRS 1778 10-12, Ave de l'Europe 78140 Velizy-Villacoublay - France

Abstract: This work deals with telepresence missions with semi-legged robots. The system is dedicated to unreachable environments for human beings. Critical situations are supervised by an operator which decides actions to be done. The operator uses a dataglove to control the robot: two fingers control the legs and the arm yaw gives the orientation. General speed is also controlled. Off-line simulation and Virtual Reality tools recreate the robot environments in a Reinforced Reality domain. Main are related to time delay and hand gesture interpretation. Fuzzy tools at low level are introduced. Such a system is discussed. Keywords: autonomous mobile robots, walking robots, robot behaviour, confined environments, telelocomotion, telepresence, dataglove, virtual reality, reinforced reality, fuzzy controllers.

1. INTRODUCTION

very well adapted to navigation tasks (teleoperation is facilitated when the general stability of the robot is overcome).

Nowadays, mobile and autonomous robots take up a great part of non manufacturing Robotics. The "Service and Intervention" fields are thought to be possible solutions where legged robots can be introduced. Different investigations are possible when dealing with legged robots and a given task. At the L.R.P. (Laboratoire de Robotique de Paris), attention has been in particular focused on problems related to the quadruped robots stability (Nakamura, et al., 1989). Such a work has been possible with a "force control and distribution" approach requiring a real time computation of the dynamic model of the system (Kjmura, et al., 1990). Another trend., which is dealed with for now, is to study legged robots with respect to various situations (different topologies, rough terrain, partially unknown environments). Such an aim requires a matching between the task to be performed and the mechanical specifications of the robot. In many cases hybrid structures (e.g.: legs plus wheels) (Villard., 1993; Fontaine, 1994) are

Nevertheless, the quasi-totality of the eXistIng applications lacks of associated technologies. Today, they are unable to provide a high degree of autonomy at low levels to mobile robots. This is the reason why it is very interesting to keep a human being in the control and command loop which includes (in the presented case) a mobile robot and its calculator. Blocked or difficult situations are supervised by a human operator which decides in a "real time" manner the next action to be done. In some other cases an automatic procedure can replace or simply ease the task of the h~an operator. This approach can be synthesised in a Telepresence System (or "tele-existence" system). Numerous tools can be used: off-line simulation tools, Virtual Reality (VR) tools to recreate the robots real environments in a Reinforced Reality domain (Bejczy, et al., 1990), and most of all fuzzy tools. 187

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Those functional aspects require at least a sensor data analysis to refresh the data-bases associated to the system. The work presented here after is issued from those very general remarks. Telepresence and telelocomotion are underlined whilst the robot is used in specific environments. Narrowness (heating sheaths ... ) or dangerousness (nuclear plants, minefields .. .) are targeted. After a brief oveniew of the mechanical abilities of the robot, the way to teleoperate the system is explained for this application, some (human) interfaces (issued from medical studies of the hand) are presented (currently under development). Besides, the system is not totally anthropomorphic and fuzzy rules are necessary to transmit to the robot the data coming from high levels like general beha,iour as well as the operator gesture. Such a solution provides also an open field of research in terms of human training before performing critical tasks.

2. A SEMI-LEGGED ROBOT FOR TELELOCOMOTION A mini semi-legged mobile robot called RAMSES (French acronym for a Mobile Autonomous Robot with an Advanced System of Support) has been developed (Fontaine, 1994). This robot has front legs and wheels at the rear (Fig. I). It is able to walk (and roll ... ) in an automatic or teleoperated mode to realise what is so-called "Telelocomotion" (Kheddar 1995)

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This type of robot allows a quasi-unconditional stability if it is considered that the lateral displacement of the centre of gravity is limited by the presence of the wheels. This mechanical system has been designed keeping in mind small obstacles avoidance under teleoperation routines. In the second version of RAMSES (Fig. 2), front legs (composed of two controlled pneumatic cylinders) are dedicated to direction and support while the motorised wheels provide the necessary torque for the movement. It is necessary to teleoperate the robot with the most direct relation between the operator and the mobile in order to provide an ergonomic human-robot interface. The movement is produced by a dataglove (Fig. 3) which covers the hand of the operator (Fontaine, 1994). The legs of the robot copy the operator fingers movement (Fig. 4).

This approach is extended to determine classes of equivalence between a human operator and the existing (or future) range of semi-legged robots developed (Kheddar 1995). With this aim, it is possible to derive in which cases it is possible to have a direct relation (in terms of morphology) between the robot and the human operator. The study of the human-robot interface must determine when an extra effort from the operator is required and finally. when it is totally inconceivable. Obviously, a very efficient way to teleoperate a system can be a Telepresence system which uses modern tools (e.g. Virtual Reality), and as far as possible direct relations between the human abilities (physical and psychological ones) and the robots characteristics.

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The denoted angle between the hand and the arm was given according to an ergonomic consideration: the finger flexion (needed in the "walking" attitude) is possible only with a wrist in extension (20° are optimal for a total flexion as in gripping function) (Tubiana and Thomine, 1990).

The presented system gives encouraging results in terms of navigation in real or virtual world. However, the motorization of the wheels is redesigned. For that, a cinematic and dynamic simulation software (SDS : Solid Dynamic Software) enables the evaluation of some "Follow The Leader" techniques for the wheels in order to facilitate different obstacle avoidances.

Different types of datagloves are available according to the desired precision level. It is possible to use either a glove with hasty information (e.g. a PowerGlove from Nintendo) when on-off systems are sufficient (Fontaine, 1994), or to prefer a precise device in order to provide more discriminating data to control the robot legs. A glove of the latter type, composed with strain gauges, is now evaluated on RAMSES IT (Fig. 6). One gauge is placed above each finger articulation (3 for the index and the middle finger, 2 for the thumb), on a thin steel blade. The blade is placed into a pocket fixed on the glove.

3. SOME TELEPRESENCE DEVICES During the teleoperation mode, the operator is fitted out with a three-finger dataglove (the third one is dedicated to gripping sequences or moving forwards or backwards) to control the walking robot: two fingers are used to control the two legs by finger flexion interpretation. The robot speed is controlled directly by the finger flexion speed. For visual feedback, the operator is assisted by a method which keeps his hands free . The environment is re-created in conjunction with "virtual cameras" fixed to the robot or according to the choice of the operator.

During a finger flexion, the blade, fixed above the finger tip, slides into the pocket. The gauges, pressed between the articulation and the outer part of the pocket, measure the blade deformation and then the flexion.

The robot direction is determined according to the yaw of the arm proximal part around a fixed (vertical) axis through the wrist. The work of Tubiana and Thornine (1990) about the hand functional anatomy permits to demonstrate that it is not possible to use the wrist yaw itself to command the robot direction: the wrist lateral movements have a higher range inwards (approximately 35°) than outwards (about 15°).

4. FUZZY TOOLS Designing a dataglove, all the difficulty lies in the transformation from the fingers movement into the legs motion: on one hand it deals with an operator behaviour though in the other hand it is a question of motion law. Indeed, the operator confirms with the finger movements (a general attitude) a declared behaviour for the robot (e.g. "walk straight ahead". ..). The matching between the movements interpretation and the declared behaviour must be checked before the command laws construction. Obviously, it is possible but not optimal (lot of calculus) to obtain a deterministic command law because the strain gauges are coupled. It is then interesting to have a fuzzy approach to reach that target. Moreover, if the operator indicates the behaviour the robot must follow, the robot has to return interpretable feedbacks. In those two cases a fuzzy control is suggested (Lee, 1990a, b).

Assuming that the operator is in a fixed telepresence system, a special device for telelocomotion is proposed (Fig. 5): it is composed by a cradle which firmly maintains the hand, the wrist and the proximal part of the arm. A pivot point for the yaw is under the wrist. A dataglove covers the operator's hand The "walking" movement of the fingers is eased by a kind of passive conveyor belt which can give a force feedback under the finger tips in a future version. YawlAxiS ;

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Fig. 7. Software and hardware architectures ofRAMSES II In Figure 7 the hardware architecture of RAMSES II is described. The main controller is designed with two levels: a master fuzzy micro-controller interprets data coming from the telelocomotion device and translate them into inputs for the low-level controllers: it fuzzifies. defuzzifies and discriminates in order to generate a position for each leg. This position is interpreted by the corresponding lowlevel micro~ontroller to provide the position of each cylinder to the dedicated leg control card.

Virtual reality can be used to perform fuzzy control rules (laws) based on robot behaviour simulations. The operator uses a dataglove to make the robot walk in an imaginary environment modelled graphically with some obstacles or in a chaotic way: classical control laws (based on model equations) cannot be defined easily, due to their complexity or time processing consuming. The perturbations of the environment on the robot (walking) tasks are perceived by the operator who performs an intuitive and reactive control. If he fails (the robot becomes unstable and falls) the operator can repeat the sequence until he is successful or decides that this situation is not relevant.

It must be noted that this architecture is modular and permits to integrate feedback data from additional sensors implanted on the legs. Indeed, the use of the conveyor belt strictly depends on the availability of belt/foot contact sensor.

During this learning phase. a high level software supervisor records the reactive control parameters (e.g. rotation, motor torque, leg flexion ... ) versus external perturbations (wind, ground elevation, ... ).

Before performing intervention or inspection tasks, the operator must be trained to teleoperate the robot, in order to learn how to take a decision when looking at the behaviour of the robot. In a virtual environment, events that occur can be reproduced during simulation phases. The way to react can be pre-programmed, If the operator fails. the situation can be reproduced until he is succeeding or ask for a computer simulation assistance. The operator acquires experience and performs easily telepresence intervention tasks in real environments. 190

The supervisor software establishes rules of control based on human control law. In the supenisor an algorithm crosses all the rules established in simulation and performs a fuzzy array of control rules (Zadeh, 1973). This is made "ith the hypothesis that input/output and world parameters are fuzzified before simulation. We plan to use this concept also to "fuzzify" the parameters but in this case the algorithm becomes more complicated.

The validation of this approach can be done by reproducing the real environment and testing the fuzzy laws on the robot in an autonomous mode.

Nakamura, T. , K. Nagani, and T. Yoshikawa (1987). Dynamics and stability in coordination of multiple robotic mechanisms. In: The Int. J. ofRobotics Research, Vol. 8 N° 2, pp. 44-61.

5. CONCLUSION

Tubiana, R. and J.-M. Thomine (1990). La Main,'

anatomie fonctionnelle et examen clinique. The work presented in this paper is a first step towards an ergonomic system of telepresence with a small robot where the general dimensions of the legs are within the dimensions of human fingers. For now, the system is not totally anthropomorphic for many (good) mechanical considerations. These reasons have stressed out the fact that a fuzzy controller is necessary at low level to avoid non acceptable hand gesture interpretations.

Masson, Paris, France. Villard, C. (1993). Etude du comportement dynamique d'un robot quadrupede. In: PhD Thesis, Universite Pierre et Marie Curie. Paris. Zadeh, LA (1973). Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. In: IEEE Transactions on Systems, Man, Cybernetics, Vol. 3, No. 1, pp. 28-44.

Most of the devices presented are working very efficiently, only the conveyor belt is under development. Our goal is now to get feedback information coming from the legs. For that we will focus our attention designing sensors attached to the legs and wheels in order to get force feedback on a glove already developed in the laboratory.

REFERENCES Bejczy, A. , W. Kim and S. Venema (1990). The Phantom Robot: Predictive Displays for Teleoperation with Time Delay. In:

Proceedings of 1990 IEEE International Conference on Robotics and Automation. Cincinati, Ohio. Fontaine, J.-G., N. Cislo, S. Buchheit, M. Guihard and P. Gorce (1994). How to Walk and Roll with a Real or Virtual Robot. In: Euriscon' 94 European Conference, pp. 1841-1846. Malaga, Spain. Lee, C.C. (1990a). Fuzzy Logic in Control Systems: Fuzzy Logic Controller - Part I. In: IEEE

Transactions on Systems, Man, Cybernetics, Vol. 20, No. 2, pp. 404-418. Lee, C.C. (1990b). Fuzzy Logic in Control Systems: Fuzzy Logic Controller - Part 11. In: IEEE

Transactions on Systems, Man, Cybernetics, Vol. 20, No. 2, pp. 419-435 . Kheddar, A. , N. Cislo, D. Talaba and J.-G. Fontaine, (1995). Several Mechanical Architectures for Telepresence with Semi-Legged Mobile Robots. In: Proceedings of the Ninth World Congress

on the Theory of Machines and Mechanisms IFTOMM'95, to be published. Milano, Italy. Kimura, H. , I. Shimoyama and H. Miura (1990). Dynamics in the dynamic walk of a quadruped robot. In: Advanced Robotics 4, pp. 283-301. 191