- Email: [email protected]
Realtime Control in Factory Automation
Copyright © IFAC Algorithms and Architectures for Real-Time Control, Vilamoura, Portugal, 1997
REALTIME CONTROL IN FACTORY AUTOMATION
P. Kopacek
Institute for Handling Devices and Robotics Vienna University o/Technology Floragasse 7a. A-J040 Vienna. AUSTRIA Tel: +43-1-5041835. FAX: +43-1-5041835-9 e-mail: [email protected]
Abstract: Automation today consists of two main fields: the automation of continuos processes - process automation- and the automation of discontinuous processes production automation. Both fields get closer together under the influence of microelectronics or modem computing. In both fields AI methods are introduced. This leads to new headlines in factory automation, like intelligent manufacturing systems (ims), service robots, with new tasks for real time control. Keywords: Real time control, manufacturing automation, Robots
1. INTRODUCTION
control in chemical and process engineering, electric power generation, position control in navigation and in biomedicine.
Some "tools" of manufacturing automation and robotics necessary for realtime control will be shortly presented.
1.2 Man - Machine Communication 1.1 Trends in realtime process control
The user interfaces in process automation systems get more and more user friendly because of developments in "Man Machine Communication (MMC)" an absolutely necessary tool for real time control. Fully graphic screens operated by mouse or joystick, logical cross checks (thinking systems) and the possibility to generate a distinct layout by users are available. Such user friendly interfaces require an improved computer hardware - storage capacity, clock frequency (computing speed )
Process automation or the automation of continuos processes is and will be dominated by "classical" control engineers. Therefore topics like adaptive control, nonlinear or timevarying systems, identification and parameter estimation and advanced control algorithms are on top. Some years ago the first intelligent sensors and actuators, equipped with one chip microprocessors, were commercially available. Furthermore modem computing technologies make it possible to realize modem control concepts like adaptive or "advanced" control algorithms . The main problem is which control method should be applied for distinct realtime tasks. According to a study some years ago, "advanced" algorithms are used for aircraft control,
1.3 ArtifiCial Intelligence Artificial Intelligence - AI - is since some decades an ex1ensive research field. The first knowledge based or expert systems were available in the late seventies preferably for special fields in medicine. One of the 15
reasons was the computer hardware because AI methods require very high computer power. In the last years the computer capacity increases dramatically - especially from PC's - and therefore some methods of "Artificial Intelligence - AI" can be applied in an efficient way for real industrial processes. For such purposes programming languages and software tools are available for "low cost" industrial applications.
1.4 External sensors Autonomously or (partly autonomously) guided systems need to move in an unstructured environment without having a-priori knowledge. Regarding to economical reasons, one is interested to increase the autonomy of these systems so that they can take over some tasks of the operator, who again can spend his time for other, more special tasks. To provide this autonomy, there is a need for sensor based guidance - thinking in terms of "low~st" solutions - operating on the base of ultrasonic sensors.
One of the "magic terms" in automation in the last years was "fuzzy". Created by the mathematician Lotfi Zadeh approximately 30 years ago and introduced in automation in the early eighties by the Japanese. In Europe - with the usual dead time - ten years later fuzzy logic and fuzzy control become headlines. A lot of industrial applications appears in a short time - most of them only for ,,PR" purposes and nearly every producer of control devices has at least one with the label "fuzzy". In process automation fuzzy control can be used for the control of highly nonlinear processes, time varying systems, multivariable control systems and for modeling and identification of some complex processes. Today fuzzy methods are mainly used for control tasks in household and utility goods, adaption of controller parameters, as modules for PLC' s and microcomputer controllers. Future applications could be classification and pattern recognition, fuzzy techniques for expert systems, neuro-fuzzy techniques, fuzzy techniques for Petri-Nets. The efficiency of fuzzy methods depends mainly from the quality of the rule base. Furthermore no stability criteria and only few optimization methods for fuzzy controllers are published.
The "smart sensors" concept is based on the idea to use animal behaviour as a paradigm for the control of man-made machines. Analyzing the complex behaviour of animals or human beings, one can isolate releasing mechanisms that cause a specific response to certain situations. The design of these behaviours can be considered as a fast human copy of the evolution process resulting in reliable and efficient control systems (Fig. 1).
Sensor Design Physical Sensor Configuratio
Smart Sensor Sensor Management Behaviour Control
Fig. 1. Smart Sensor Concept (probst, 1996). At behaviour control each control system is implemented as an independent module that generates a special response as a function f of the input of sensors and other modules (f = f(xI, xl), with xl is the input of the sensors and xl is the status of the other modules). It can be processed parallel to other Behaviour Modules - these modules communicate via messages to each other. To manage conflicts, the input information can be inhibited by another behaviour or an output response can be suppressed.
Artificial neural networks (ANN) for control purposes were introduced a little bit later than fuzzy methods. The original idea was to copy some parts of the human brain; e.g. a neural net is able to learn from the environment. Applications are in robotics, in steel production, in paper industry and in banking. The field of applications for neural nets are not so clear defined than for fuzzy concepts. Both concepts are merged to neuro-fuzzy in the last time. Neuro-fuzzy is a combination of the ability to learn from the neural nets and the transparency of fuzzy methods. Today only few pilot applications are known e.g. control of a washing machine, adaptive control of steam generator and control of a grinding process. These developments yield to new subjects in automation like genetic algorithms. neuroinformatics and soft computing.
Classical approaches of control systems for mobile robots are typically of a cascaded structure. Any changes of the lower levels do have an influence to the higher ones. The structure of a "Behaviour Control" is similar to the Object-Oriented approach: A behaviour is an abstraction of a set of rules that generate the specific response to a specific stimulus.
16
A ..Behaviour Module" receives messages from and sends messages to other modules. The internal infonnation processing is hidden - this encapsulation allows an easy maintenance of the modules. The modules can be developed in parallel and the adaptation to application-specific requirements can simply be done by adding new behaviour modules.
2.1 "Low cost" Computer Integrated Manufacturing
Especially SME's had a lot of difficulties to introduce ClM or parts of CIM. Today only in few SME's a total ClM concept is realized. In most of the SME's only some ClM components (CAD, CAP, CAM, CAQ, PPS) or parts of these are realized. European and especially Austrian SME's need more time to get familiar with the ClM philosophy and to introduce more components or parts of them.
An ultrasonic sensor system used for the autonomous guidance is required to reliably detect a vast variety of objects. The degree of reflection of the ultrasonic energy differs from almost 100% for a huge plane wall perpendicular to the acoustical axis of the sensor down to 20010 for the legs of a hwnan being or even 1% for a tiny object such as the leg of a chair. "Smart Sensors", the combination between sensor element and behaviour control, are designed for the reliable and robust execution of sensor based functions in the real world.
Software packages for the ClM components are available commercially from various sellers. Usually these packages are only partially suitable for SME's. They offer a lot of features, often not necessary for the demands of SME's, on the other hand features necessary are missing. Adding some of these takes a long time and it is usually very expensive. Furthermore most of these packages requires a cost intensive computer hardware.
2. COMPUTER INTEGRATED
MANUFACTURING Especially for the demands of SME's flexible, modular "low cost" ClM concepts are necessary. From the side of hardware, the basic philosophy is to use PC's (e.g. 486 compatibles or similar) connected by a local area network (LAN) with a host computer for database tasks. The operating system for the PC's is MS-DOS, for the host computer UNIX. As a LAN serves ETHERNET.
The field of production or manufacturing automation was dominated by ClM - Computer Integrated Manufacturing - in the last decade. The original idea of a total computer aided or controlled production from the order or first product draft until the delivery was only realized in few cases worldwide mainly in large companies. According to common definitions, ClM consists of the following components:
The modular "low cost" ClM concept is shown in Fig.2. It uses two types of computers: A UNIX machine serves as a database and network server, various MS-DOS computers (AT or 386) work as network stations with different tasks. For OCA special terminals are used.
CAD: includes all data processing activities, related to development and construction, together with calculation and simulation (CAE) CAP: planning of work. programming of NC machines (results are basic data of the PPS system).
The database-server and all workstations are connected by a local area network (ETHERNET). A second network (party-line) connects the OCAterminals with the OCA-server, which works as an intelligent gateway between the two networks.
CAM: includes the support of computers for the control of the working means during the production (machine tools, handling devices, transport and stock systems).
The various control systems recognize on their own, if the connection to the host server is possible and/or succeeded. They build up the connections self-acting and adjust the data between the different databases automatically.
CAQ: describes computer supported planning and performance of quality control.
With this solution the personnel in the production is not stressed with additional data-processing activities, in order to keep the control system working. Each workstation has its own server process running on the network server. These server processes handle the communication between workstations, processes and database. The software is completely modular. "Modules" could be commercially available or individually written
PPS: includes the use of computer aided systems for the organisatorial planning, controlling and monitoring of all processes.
17
PPS Server CAQOCA Terminals
OCAGateway
CADINC Fileserver CIM PC. ',..~... NC Machines
Fig. 2. "Low cost" CIM concept (Kopacek, 1991).
2.2 Intelligent Manufacturing Systems - "ims"
according to specific demands of the user. These modules can combined with a minimum of interface problems - as usual in CIM systems today. The programming language is C or C++.
Generally, AI methods are introduced more and more in production automation or CIM systems. This results in intelligent CIM components - ICAD, ICAP, ICAM, ICAQ - and in intelligent CIM systems (lCIM) or in intelligent manufacturing systems (ims). This new philosophy requires a lot of prerequisites and research.
This concept has following advantages: • low cost • Possibility of stepwise realization • easy combination of software modules for a specific solution • possibility to include AI methods in some modules.
"ICIM" or "ims" is partially introduced in the industry but mainly for large companies. AI in fonn of knowledge based and e},."J)ert systems is ready to be introduced in an efficient way in CIM components. The implementation of AI methods in "low cost" CIM systems depends from the availability of AI software packages for this hardware configuration.
From a control engineering viewpoint the operation of today's "Flexible Manufacturing System (FMS)" as a important CIM component is planned and openloop. This might be one of the reasons that FMS operations are not very reliable. Therefore there is a trend for introducing feedback and closed loop control techniques into FMS subsystems and operations. The incorporation of automatic tool monitoring, automatic tool change as well as closedloop quality control are some steps in this direction. A more detailed analysis of the various FMS areas shows that because of the great variety of control tasks involved , the application of standard control techniques may not be sufficient for this complex industrial environment. "Advanced" control algorithms probably with methods of artificial intelligence have to be introduced.
The results of the 6 test cases of the worldwide imsinitiative TC2 Clean manufacturing TC3 Global concurrent engineering TC4 Globeman 21 TC5 Holonic manufacturing systems TC6 Rapid product development TC7 Knowledge systemization are "tools" for the development and a new dimension in real time control.
3. ROBOTS As a typical example for the present state and future developing trends in production automation could serve the industrial robot. Robots were 10 to 15 years
18
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Fig. 3. Comparison: Installed IR versus service robots (Schraft, 1993) ago one of the headlines in factory automation. Meanwhile robots are a tool on the manufacturing level.
Integration of industrial robots in the manufacturing environment requires enhanced capabilities of the hardware structure of the robot controller as well as the robot programming system. Related to the first aspect, fault tolerant multiprocessor architectures represent a perforrnant solution, for nowadays multitasking robot controllers. Robot languages integrate sensory-based commands for adaption to the working environment.
3.1 Industrial robots The worldwide robot population was growing up dramatically in the last years. Approximately ten years ago the number of robots in industry were nearly doubled every three years. Therefore according to the forecasts five years ago the number of robots working in industry world-wide should be increased 30% every year. One of the reasons is that in classical application fields like spot welding, spray painting, coating, materials and parts handling a saturation can be obtained especially in the last three years. Work places requiring industrial robots are usually equipped with such robots. Three years ago the industry was waiting for the intelligent robot equipped with external sensors. As already known the development of such e:\."ternal sensors like visual, auditive, force torque etc. is going on very well in research institutes and laboratories. But until now only few of these sensor concepts are available for industrial applications at a reasonable price.
As an example could selVe a robotized assembly cell. To handle all the necessary different assembly sequences a hierarchical control structure was chosen as shown in Fig. 4. At the lowest level there are only local control functions, which are divided into subsystems with own controllers such as: -7 Robots -7 Screwing devices -7 Soldering device
and Systems without controller like: -7 Transportation system -7 Part feeders All these subsystems interface to the sequence controller. This module is connected to a database containing the following informations: • All single robot programs • Start conditions for one part • Definition of the sequence of assembly • Information for plausibility check of robot program and tooVgripper • Information about the used storing devices or tools. • Information to avoid collision.
Therefore between 1992 and 1994 the producers of industrial robots were confronted with a decreasing demand of industrial robots. The number of installed robots in the industry worldwide was approximately 30 % less than the estimations five years ago. As a logical consequence the prices for industrial robots decreases in these years dramatically. Latest developments deal with a modularisation of the robots as well as the control system. Probably in two or three years it might be possible to buy an industrial robot and separately from another company an advanced control computer at low prices.
The tasks of the sequence controller are to check the availability of all components in each stage of the assembly process, to start the corresponding robot program sequence and to send all the necessary
19
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toCIM (Ethernet • lAN)
Man-MachineInterface
Robotcontrollers
Partfeeder
Transportation systems
Sensordatas
Tools
TooI-ChangingSystems Grippers
external controllers
Screwing de.;c,;s Soldering and Glueing devices
Fig. 4. Control Structure of an Assembly Cell (probst, 1996) 3.2 Service Robots
commands to the connected subsystems. On the other hand the sequence controller is connected to a man-machine-interface. All error and statusconditions are interfaced to this module.
Producers of industrial robots tried to recognize new application areas. A broad field are so-called unconventional areas. This unconventional areas can be divided in two classes:
The module for collision avoidance is mainly responsible for the coordination of all assembling operations where both robots are involved (e.g. one robot move a wire towards the surface of the printed circuit, the other solders the two parts.). Furthennore this module watches all parallel moving sequences of the robots and stops one, until the other robot reaches the same point within the assembling sequence. The Man-Machine-Interface module displays all error conditions and status infonnations of the cell and generates automatically report-files.
•
Robots to replace human beings at work in dirty, hazardous and/or tidious operations
•
Robots to operate on human beings to elevate incornodity or to increase comfort pleasure.
To the first category what is necessary for: • Operation in hazardous environment (e.g. in high temperature, vacuum, underwater, radioactive environment) • Fire fighting (fire extinction, life saving) • Police applications • Military applications • Architecture (inspection/maintenance of buildings/structures) • Publicity (attracting customers, etc.) • Entertainment (appearance in films) • Housework (floor sweeping, cooking)
Therefore future industrial applications of industrial robots can be divided in two directions. On the one hand side intelligent robots are necessary for increasing the number in classical application fields. In addition to the application fields mentioned before some other classical fields growing up dramatically in the last two years, e.g. assembling as well as disassembling. For disassembling applications new features of the industrial robots are necessary. These robots require a combined position and force control as well as relatively high payload. That requires the availability of cheap ex"ternal sensors in the nex"t years for industrial applications.
To the second category robots can applicate in the following fields: • Medicine (patient care)
20
• • •
additional features like combined force and position control, external sensors based on microsystems, flexible and light weight robots. Because of the decreasing number of installed robots new application fields will be recognized. One of these fields are the service robots. Service robots look quite different than conventional and therefore research have going on in additional directions such as external sensors, new grippers and gripping devices, new kinematic structures. Efforts have to be undertaken to further develop key components of these robots towards efficiency, performance, miniaturization and cost. Here the collaboration of research institutions, service industry and robot and component manufacturers has the potential to create valuable synergies.
Guiding the blind Entertainment (use in gaming houses, in amusement parches) Housework (table services)
Comparing with industrial robots, service robots would be characterized by the following facilities, to permit the operating effectively and unobtrusively in the human living environment: • Mobility • Portability • Operating case • Sensingllearning/judging functions (artificial intelligence) • Adaptability to widely varying operations and environmental conditions The ultimate target to be reached would be a robot that possesses faculties approaching that of human beings. Leaving such an ideal robot as a goal for the future, intennediate robots that only satisfy a limited selection of the most requisite functions should still find good use in human society. Among the faculties cited above, what is the most indispensable for a service robot would be mobility.
4. SUMMARY
Microelectronics is the driving force to close the historical gap between theory and practice in automation. We are now in the position to realize modem control concepts like "advanced" control algoritluns, fuzzy methods, neural networks, expert or knowledge based systems but we have no e~:perience when such a modem concept is necessary and efficient.
Today the number of service robots in operation is very small. However, the evolution of people working in the service field shows a constant growth rate and consequently enormous potential. Great hopes are attached to the e~:pansion of this sector, however the possibility of the automated implementation of services through robot systems is barely apparent, neither to the supplier and manufacturer, nor t9 the user/customer. The use of robot systems in the field of services offers, in principle, advantages to all those involved.
The future of automation in the broadest sense will be determined by the development of microcomputers e.g. single chip processors from the hardware side. The software tends towards "user friendly" with all advantages and disadvantages. Advantages are e.g. the possibility in process control systems to create an own layout for the process or to develop an own e~:pert system for a special purpose. Disadvantages are the higher computer power for this tasks as well as the complexity of the new software tools.
To fulfill these tasks, research would be necessary in the nearest future in the field of microsystems or micro-mechanics. Microsystems or micro-mechanics is an interdisciplinary research field growing up dramatically in the last five years. As a research field between mechanical engineering, electronics, computer science, Microsystems should be applicable in the nearest future for industrial robots.
Introduction of methods of AI in automation is in progress and will be increasing in the future. New control concepts like neural networks and genetic algoritluns are introduced in industrial applications in the nearest future. The next generation is ready from the theory and waits for practical applications.
Another direction taken in service robot development is toward limited purpose robots to serve such specific purposes as • guiding the blind • patient care • floor sweeping • building/civil construction work • inspection, operation.
The future of production automation is dominated by "new" headlines like intelligent manufacturing systems, agile manufacturing, holonic systems, rapid prototyping, etc.). Historically production automation was always and will be in the future the field of headlines. In reality we have to introduce as pointed out in the paper - AI methods, starting on a very low level, in this field of automation. This development requires new and advanced realtime control concepts.
Future application oriented research in robotics is dominated by two mean directions. Robots for classical applications have to be equipped with
21
5. LITERATURE
Kopacek, P., A. Frotschnig. and V. Kacani (1991). User interface to a CIM-database. In: Proceedings of the Second International Workshop on " Computer Aided Systems Theory EUROCAST'9I". Lecture Notes in Computer Sciences, Vol. 585, pp. 592-601. Springer Verlag, Krems. Kopacek, P. (1994). Robotics research today and in the future. In: Preprinls of the Symposium "Robotics in Alpe Adria Region - RAA 1994", p. 213-217. Bled. Kopacek, P. (1995). Trends in process and production automation from the viewpoint of European small and medium sized companies. Bulletin of the Polytechnic Institute of Iasi Vol. 45, pp. 7-21. Probst, R and P. Kopacek (1992). Robotized assembly cells in low cost CIM concepts. In: Proceedings of the 23rd "International Symposium on Industrial Robots - ISIR'92", p. 191-195. Barcelona. Probst, R and P. Kopacek (1996). Service robots Present situation and future trends. In: Proceedings of the 2nd ECPD International Conference on "Advanced Robotics. Intelligent Automation and Active Systems ". Vienna. Schmidt, G. (1991). Towards integration of autonomous subsystems for assembly and mobility into flexible manufacturing. In: Proceedings of the Int. Workshop "Information Processing in Autonomous Mobile Robots", pp.3-20. Springer. Schraft, RD. (1994). Service Robots: Opportunities, Possibilities and Potentials for the Ne:\.1 Decade. In: Proceedings of the " IEEE Robotics Conference ". San Diego.
22
REALTIME CONTROL IN FACTORY AUTOMATION
P. Kopacek
Institute for Handling Devices and Robotics Vienna University o/Technology Floragasse 7a. A-J040 Vienna. AUSTRIA Tel: +43-1-5041835. FAX: +43-1-5041835-9 e-mail: [email protected]
Abstract: Automation today consists of two main fields: the automation of continuos processes - process automation- and the automation of discontinuous processes production automation. Both fields get closer together under the influence of microelectronics or modem computing. In both fields AI methods are introduced. This leads to new headlines in factory automation, like intelligent manufacturing systems (ims), service robots, with new tasks for real time control. Keywords: Real time control, manufacturing automation, Robots
1. INTRODUCTION
control in chemical and process engineering, electric power generation, position control in navigation and in biomedicine.
Some "tools" of manufacturing automation and robotics necessary for realtime control will be shortly presented.
1.2 Man - Machine Communication 1.1 Trends in realtime process control
The user interfaces in process automation systems get more and more user friendly because of developments in "Man Machine Communication (MMC)" an absolutely necessary tool for real time control. Fully graphic screens operated by mouse or joystick, logical cross checks (thinking systems) and the possibility to generate a distinct layout by users are available. Such user friendly interfaces require an improved computer hardware - storage capacity, clock frequency (computing speed )
Process automation or the automation of continuos processes is and will be dominated by "classical" control engineers. Therefore topics like adaptive control, nonlinear or timevarying systems, identification and parameter estimation and advanced control algorithms are on top. Some years ago the first intelligent sensors and actuators, equipped with one chip microprocessors, were commercially available. Furthermore modem computing technologies make it possible to realize modem control concepts like adaptive or "advanced" control algorithms . The main problem is which control method should be applied for distinct realtime tasks. According to a study some years ago, "advanced" algorithms are used for aircraft control,
1.3 ArtifiCial Intelligence Artificial Intelligence - AI - is since some decades an ex1ensive research field. The first knowledge based or expert systems were available in the late seventies preferably for special fields in medicine. One of the 15
reasons was the computer hardware because AI methods require very high computer power. In the last years the computer capacity increases dramatically - especially from PC's - and therefore some methods of "Artificial Intelligence - AI" can be applied in an efficient way for real industrial processes. For such purposes programming languages and software tools are available for "low cost" industrial applications.
1.4 External sensors Autonomously or (partly autonomously) guided systems need to move in an unstructured environment without having a-priori knowledge. Regarding to economical reasons, one is interested to increase the autonomy of these systems so that they can take over some tasks of the operator, who again can spend his time for other, more special tasks. To provide this autonomy, there is a need for sensor based guidance - thinking in terms of "low~st" solutions - operating on the base of ultrasonic sensors.
One of the "magic terms" in automation in the last years was "fuzzy". Created by the mathematician Lotfi Zadeh approximately 30 years ago and introduced in automation in the early eighties by the Japanese. In Europe - with the usual dead time - ten years later fuzzy logic and fuzzy control become headlines. A lot of industrial applications appears in a short time - most of them only for ,,PR" purposes and nearly every producer of control devices has at least one with the label "fuzzy". In process automation fuzzy control can be used for the control of highly nonlinear processes, time varying systems, multivariable control systems and for modeling and identification of some complex processes. Today fuzzy methods are mainly used for control tasks in household and utility goods, adaption of controller parameters, as modules for PLC' s and microcomputer controllers. Future applications could be classification and pattern recognition, fuzzy techniques for expert systems, neuro-fuzzy techniques, fuzzy techniques for Petri-Nets. The efficiency of fuzzy methods depends mainly from the quality of the rule base. Furthermore no stability criteria and only few optimization methods for fuzzy controllers are published.
The "smart sensors" concept is based on the idea to use animal behaviour as a paradigm for the control of man-made machines. Analyzing the complex behaviour of animals or human beings, one can isolate releasing mechanisms that cause a specific response to certain situations. The design of these behaviours can be considered as a fast human copy of the evolution process resulting in reliable and efficient control systems (Fig. 1).
Sensor Design Physical Sensor Configuratio
Smart Sensor Sensor Management Behaviour Control
Fig. 1. Smart Sensor Concept (probst, 1996). At behaviour control each control system is implemented as an independent module that generates a special response as a function f of the input of sensors and other modules (f = f(xI, xl), with xl is the input of the sensors and xl is the status of the other modules). It can be processed parallel to other Behaviour Modules - these modules communicate via messages to each other. To manage conflicts, the input information can be inhibited by another behaviour or an output response can be suppressed.
Artificial neural networks (ANN) for control purposes were introduced a little bit later than fuzzy methods. The original idea was to copy some parts of the human brain; e.g. a neural net is able to learn from the environment. Applications are in robotics, in steel production, in paper industry and in banking. The field of applications for neural nets are not so clear defined than for fuzzy concepts. Both concepts are merged to neuro-fuzzy in the last time. Neuro-fuzzy is a combination of the ability to learn from the neural nets and the transparency of fuzzy methods. Today only few pilot applications are known e.g. control of a washing machine, adaptive control of steam generator and control of a grinding process. These developments yield to new subjects in automation like genetic algorithms. neuroinformatics and soft computing.
Classical approaches of control systems for mobile robots are typically of a cascaded structure. Any changes of the lower levels do have an influence to the higher ones. The structure of a "Behaviour Control" is similar to the Object-Oriented approach: A behaviour is an abstraction of a set of rules that generate the specific response to a specific stimulus.
16
A ..Behaviour Module" receives messages from and sends messages to other modules. The internal infonnation processing is hidden - this encapsulation allows an easy maintenance of the modules. The modules can be developed in parallel and the adaptation to application-specific requirements can simply be done by adding new behaviour modules.
2.1 "Low cost" Computer Integrated Manufacturing
Especially SME's had a lot of difficulties to introduce ClM or parts of CIM. Today only in few SME's a total ClM concept is realized. In most of the SME's only some ClM components (CAD, CAP, CAM, CAQ, PPS) or parts of these are realized. European and especially Austrian SME's need more time to get familiar with the ClM philosophy and to introduce more components or parts of them.
An ultrasonic sensor system used for the autonomous guidance is required to reliably detect a vast variety of objects. The degree of reflection of the ultrasonic energy differs from almost 100% for a huge plane wall perpendicular to the acoustical axis of the sensor down to 20010 for the legs of a hwnan being or even 1% for a tiny object such as the leg of a chair. "Smart Sensors", the combination between sensor element and behaviour control, are designed for the reliable and robust execution of sensor based functions in the real world.
Software packages for the ClM components are available commercially from various sellers. Usually these packages are only partially suitable for SME's. They offer a lot of features, often not necessary for the demands of SME's, on the other hand features necessary are missing. Adding some of these takes a long time and it is usually very expensive. Furthermore most of these packages requires a cost intensive computer hardware.
2. COMPUTER INTEGRATED
MANUFACTURING Especially for the demands of SME's flexible, modular "low cost" ClM concepts are necessary. From the side of hardware, the basic philosophy is to use PC's (e.g. 486 compatibles or similar) connected by a local area network (LAN) with a host computer for database tasks. The operating system for the PC's is MS-DOS, for the host computer UNIX. As a LAN serves ETHERNET.
The field of production or manufacturing automation was dominated by ClM - Computer Integrated Manufacturing - in the last decade. The original idea of a total computer aided or controlled production from the order or first product draft until the delivery was only realized in few cases worldwide mainly in large companies. According to common definitions, ClM consists of the following components:
The modular "low cost" ClM concept is shown in Fig.2. It uses two types of computers: A UNIX machine serves as a database and network server, various MS-DOS computers (AT or 386) work as network stations with different tasks. For OCA special terminals are used.
CAD: includes all data processing activities, related to development and construction, together with calculation and simulation (CAE) CAP: planning of work. programming of NC machines (results are basic data of the PPS system).
The database-server and all workstations are connected by a local area network (ETHERNET). A second network (party-line) connects the OCAterminals with the OCA-server, which works as an intelligent gateway between the two networks.
CAM: includes the support of computers for the control of the working means during the production (machine tools, handling devices, transport and stock systems).
The various control systems recognize on their own, if the connection to the host server is possible and/or succeeded. They build up the connections self-acting and adjust the data between the different databases automatically.
CAQ: describes computer supported planning and performance of quality control.
With this solution the personnel in the production is not stressed with additional data-processing activities, in order to keep the control system working. Each workstation has its own server process running on the network server. These server processes handle the communication between workstations, processes and database. The software is completely modular. "Modules" could be commercially available or individually written
PPS: includes the use of computer aided systems for the organisatorial planning, controlling and monitoring of all processes.
17
PPS Server CAQOCA Terminals
OCAGateway
CADINC Fileserver CIM PC. ',..~... NC Machines
Fig. 2. "Low cost" CIM concept (Kopacek, 1991).
2.2 Intelligent Manufacturing Systems - "ims"
according to specific demands of the user. These modules can combined with a minimum of interface problems - as usual in CIM systems today. The programming language is C or C++.
Generally, AI methods are introduced more and more in production automation or CIM systems. This results in intelligent CIM components - ICAD, ICAP, ICAM, ICAQ - and in intelligent CIM systems (lCIM) or in intelligent manufacturing systems (ims). This new philosophy requires a lot of prerequisites and research.
This concept has following advantages: • low cost • Possibility of stepwise realization • easy combination of software modules for a specific solution • possibility to include AI methods in some modules.
"ICIM" or "ims" is partially introduced in the industry but mainly for large companies. AI in fonn of knowledge based and e},."J)ert systems is ready to be introduced in an efficient way in CIM components. The implementation of AI methods in "low cost" CIM systems depends from the availability of AI software packages for this hardware configuration.
From a control engineering viewpoint the operation of today's "Flexible Manufacturing System (FMS)" as a important CIM component is planned and openloop. This might be one of the reasons that FMS operations are not very reliable. Therefore there is a trend for introducing feedback and closed loop control techniques into FMS subsystems and operations. The incorporation of automatic tool monitoring, automatic tool change as well as closedloop quality control are some steps in this direction. A more detailed analysis of the various FMS areas shows that because of the great variety of control tasks involved , the application of standard control techniques may not be sufficient for this complex industrial environment. "Advanced" control algorithms probably with methods of artificial intelligence have to be introduced.
The results of the 6 test cases of the worldwide imsinitiative TC2 Clean manufacturing TC3 Global concurrent engineering TC4 Globeman 21 TC5 Holonic manufacturing systems TC6 Rapid product development TC7 Knowledge systemization are "tools" for the development and a new dimension in real time control.
3. ROBOTS As a typical example for the present state and future developing trends in production automation could serve the industrial robot. Robots were 10 to 15 years
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Fig. 3. Comparison: Installed IR versus service robots (Schraft, 1993) ago one of the headlines in factory automation. Meanwhile robots are a tool on the manufacturing level.
Integration of industrial robots in the manufacturing environment requires enhanced capabilities of the hardware structure of the robot controller as well as the robot programming system. Related to the first aspect, fault tolerant multiprocessor architectures represent a perforrnant solution, for nowadays multitasking robot controllers. Robot languages integrate sensory-based commands for adaption to the working environment.
3.1 Industrial robots The worldwide robot population was growing up dramatically in the last years. Approximately ten years ago the number of robots in industry were nearly doubled every three years. Therefore according to the forecasts five years ago the number of robots working in industry world-wide should be increased 30% every year. One of the reasons is that in classical application fields like spot welding, spray painting, coating, materials and parts handling a saturation can be obtained especially in the last three years. Work places requiring industrial robots are usually equipped with such robots. Three years ago the industry was waiting for the intelligent robot equipped with external sensors. As already known the development of such e:\."ternal sensors like visual, auditive, force torque etc. is going on very well in research institutes and laboratories. But until now only few of these sensor concepts are available for industrial applications at a reasonable price.
As an example could selVe a robotized assembly cell. To handle all the necessary different assembly sequences a hierarchical control structure was chosen as shown in Fig. 4. At the lowest level there are only local control functions, which are divided into subsystems with own controllers such as: -7 Robots -7 Screwing devices -7 Soldering device
and Systems without controller like: -7 Transportation system -7 Part feeders All these subsystems interface to the sequence controller. This module is connected to a database containing the following informations: • All single robot programs • Start conditions for one part • Definition of the sequence of assembly • Information for plausibility check of robot program and tooVgripper • Information about the used storing devices or tools. • Information to avoid collision.
Therefore between 1992 and 1994 the producers of industrial robots were confronted with a decreasing demand of industrial robots. The number of installed robots in the industry worldwide was approximately 30 % less than the estimations five years ago. As a logical consequence the prices for industrial robots decreases in these years dramatically. Latest developments deal with a modularisation of the robots as well as the control system. Probably in two or three years it might be possible to buy an industrial robot and separately from another company an advanced control computer at low prices.
The tasks of the sequence controller are to check the availability of all components in each stage of the assembly process, to start the corresponding robot program sequence and to send all the necessary
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Fig. 4. Control Structure of an Assembly Cell (probst, 1996) 3.2 Service Robots
commands to the connected subsystems. On the other hand the sequence controller is connected to a man-machine-interface. All error and statusconditions are interfaced to this module.
Producers of industrial robots tried to recognize new application areas. A broad field are so-called unconventional areas. This unconventional areas can be divided in two classes:
The module for collision avoidance is mainly responsible for the coordination of all assembling operations where both robots are involved (e.g. one robot move a wire towards the surface of the printed circuit, the other solders the two parts.). Furthennore this module watches all parallel moving sequences of the robots and stops one, until the other robot reaches the same point within the assembling sequence. The Man-Machine-Interface module displays all error conditions and status infonnations of the cell and generates automatically report-files.
•
Robots to replace human beings at work in dirty, hazardous and/or tidious operations
•
Robots to operate on human beings to elevate incornodity or to increase comfort pleasure.
To the first category what is necessary for: • Operation in hazardous environment (e.g. in high temperature, vacuum, underwater, radioactive environment) • Fire fighting (fire extinction, life saving) • Police applications • Military applications • Architecture (inspection/maintenance of buildings/structures) • Publicity (attracting customers, etc.) • Entertainment (appearance in films) • Housework (floor sweeping, cooking)
Therefore future industrial applications of industrial robots can be divided in two directions. On the one hand side intelligent robots are necessary for increasing the number in classical application fields. In addition to the application fields mentioned before some other classical fields growing up dramatically in the last two years, e.g. assembling as well as disassembling. For disassembling applications new features of the industrial robots are necessary. These robots require a combined position and force control as well as relatively high payload. That requires the availability of cheap ex"ternal sensors in the nex"t years for industrial applications.
To the second category robots can applicate in the following fields: • Medicine (patient care)
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• • •
additional features like combined force and position control, external sensors based on microsystems, flexible and light weight robots. Because of the decreasing number of installed robots new application fields will be recognized. One of these fields are the service robots. Service robots look quite different than conventional and therefore research have going on in additional directions such as external sensors, new grippers and gripping devices, new kinematic structures. Efforts have to be undertaken to further develop key components of these robots towards efficiency, performance, miniaturization and cost. Here the collaboration of research institutions, service industry and robot and component manufacturers has the potential to create valuable synergies.
Guiding the blind Entertainment (use in gaming houses, in amusement parches) Housework (table services)
Comparing with industrial robots, service robots would be characterized by the following facilities, to permit the operating effectively and unobtrusively in the human living environment: • Mobility • Portability • Operating case • Sensingllearning/judging functions (artificial intelligence) • Adaptability to widely varying operations and environmental conditions The ultimate target to be reached would be a robot that possesses faculties approaching that of human beings. Leaving such an ideal robot as a goal for the future, intennediate robots that only satisfy a limited selection of the most requisite functions should still find good use in human society. Among the faculties cited above, what is the most indispensable for a service robot would be mobility.
4. SUMMARY
Microelectronics is the driving force to close the historical gap between theory and practice in automation. We are now in the position to realize modem control concepts like "advanced" control algoritluns, fuzzy methods, neural networks, expert or knowledge based systems but we have no e~:perience when such a modem concept is necessary and efficient.
Today the number of service robots in operation is very small. However, the evolution of people working in the service field shows a constant growth rate and consequently enormous potential. Great hopes are attached to the e~:pansion of this sector, however the possibility of the automated implementation of services through robot systems is barely apparent, neither to the supplier and manufacturer, nor t9 the user/customer. The use of robot systems in the field of services offers, in principle, advantages to all those involved.
The future of automation in the broadest sense will be determined by the development of microcomputers e.g. single chip processors from the hardware side. The software tends towards "user friendly" with all advantages and disadvantages. Advantages are e.g. the possibility in process control systems to create an own layout for the process or to develop an own e~:pert system for a special purpose. Disadvantages are the higher computer power for this tasks as well as the complexity of the new software tools.
To fulfill these tasks, research would be necessary in the nearest future in the field of microsystems or micro-mechanics. Microsystems or micro-mechanics is an interdisciplinary research field growing up dramatically in the last five years. As a research field between mechanical engineering, electronics, computer science, Microsystems should be applicable in the nearest future for industrial robots.
Introduction of methods of AI in automation is in progress and will be increasing in the future. New control concepts like neural networks and genetic algoritluns are introduced in industrial applications in the nearest future. The next generation is ready from the theory and waits for practical applications.
Another direction taken in service robot development is toward limited purpose robots to serve such specific purposes as • guiding the blind • patient care • floor sweeping • building/civil construction work • inspection, operation.
The future of production automation is dominated by "new" headlines like intelligent manufacturing systems, agile manufacturing, holonic systems, rapid prototyping, etc.). Historically production automation was always and will be in the future the field of headlines. In reality we have to introduce as pointed out in the paper - AI methods, starting on a very low level, in this field of automation. This development requires new and advanced realtime control concepts.
Future application oriented research in robotics is dominated by two mean directions. Robots for classical applications have to be equipped with
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5. LITERATURE
Kopacek, P., A. Frotschnig. and V. Kacani (1991). User interface to a CIM-database. In: Proceedings of the Second International Workshop on " Computer Aided Systems Theory EUROCAST'9I". Lecture Notes in Computer Sciences, Vol. 585, pp. 592-601. Springer Verlag, Krems. Kopacek, P. (1994). Robotics research today and in the future. In: Preprinls of the Symposium "Robotics in Alpe Adria Region - RAA 1994", p. 213-217. Bled. Kopacek, P. (1995). Trends in process and production automation from the viewpoint of European small and medium sized companies. Bulletin of the Polytechnic Institute of Iasi Vol. 45, pp. 7-21. Probst, R and P. Kopacek (1992). Robotized assembly cells in low cost CIM concepts. In: Proceedings of the 23rd "International Symposium on Industrial Robots - ISIR'92", p. 191-195. Barcelona. Probst, R and P. Kopacek (1996). Service robots Present situation and future trends. In: Proceedings of the 2nd ECPD International Conference on "Advanced Robotics. Intelligent Automation and Active Systems ". Vienna. Schmidt, G. (1991). Towards integration of autonomous subsystems for assembly and mobility into flexible manufacturing. In: Proceedings of the Int. Workshop "Information Processing in Autonomous Mobile Robots", pp.3-20. Springer. Schraft, RD. (1994). Service Robots: Opportunities, Possibilities and Potentials for the Ne:\.1 Decade. In: Proceedings of the " IEEE Robotics Conference ". San Diego.
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