Abstract
This chapter presents a design methodology of discrete event distributed control architecture for autonomous mobile robot systems. A modular, behavior-based distributed software architecture is presented on a hierarchical distributed microcontroller based hardware structure for intelligent control of mobile robots. Some intelligent behaviors, such as wall following, obstacle rounding, target seeking, and local environment mapping, have been implemented using sensor control modules such as multiple infrared range finding sensor modules and motion control modules to detect walls and obstacles in the surroundings of a mobile robot, based on environment features such as lines and corners estimated using a set of range sensors and a vision sensor. Upon these behavior modules, a Petri net based approach was applied to coordination of several concurrent activities of modules for the high-level tasks such as sensory navigation in unknown environments. Task specification implies the definition of a control program composed of behavior commands, which are not expressed in a sequential fashion but implicating parallel processing control. The net model can be directly obtained from the system requirements specification of each particular application. Thus, the remaining levels of the control structure are common to a wide range of applications. The Petri net based approach validates the implementation of synchronization and coordination in discrete event behavior-based control. Behavior modules are composed to design more complex modules according to applications. The detailed function of each control module is specialized according to the application, so that new control strategies can be easily embedded in the control modules for real-time performance of robotic actions. Compared to hand–written coding in robot program, because of explicit representation of robotic actions, behaviors and tasks, the system design procedure facilitates the understanding of the interaction among the different processes that might be present in the mobile robot control system. Consequently, it is easy and computationally inexpensive to design, write, and debug planned tasks. Besides it is possible to verify structural and behavioral properties of these programs owing to formal specification.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arkin R (1987) Motor schema based navigation for a mobile robot: an approach to programming by behavior. In: IEEE international conference on robotics and automation, Raleigh, NC, pp. 264–271
Arkin R (1998) Behavior-based robotics. The MIT Press, Cambridge
Azar AT, Vaidyanathan S (2015a) Handbook of research on advanced intelligent control engineering and automation. Advances in computational intelligence and robotics (ACIR) book series, IGI Global, USA
Azar AT, Vaidyanathan S (2015b) Computational intelligence applications in modeling and control. In: Azar AT, Vaidyanathan S (eds) Studies in computational intelligence, vol 575. Springer, Germany
Azar AT, Vaidyanathan S (2015c) Chaos modeling and control systems design. Studies in computational intelligence, vol 581. Springer, Germany
Azar AT, Zhu Q (2015) Advances and applications in sliding mode control systems. Studies in computational intelligence, vol 576. Springer, Germany
Brooks RA (1986) A robust layered control system for a mobile robot. IEEE J Robot Autom 2:14–23
Brooks RA (1987) Asynchronous distributed control system for a mobile robot. In: SPIE conference on mobile robots, vol 0727, pp 77–84
Caccia M, Coletta P, Bruzzone G, Veruggio G (2005) Execution control of robotic tasks: a Petri net based approach. Control Eng Pract 13(8):959–971
Caloini A, Magnani GA, Pezze M (1998) A technique for designing robotic control systems based on Petri nets. IEEE Trans Control Syst Technol 6(1):72–86
Connell J (1992) A hybrid architecture applied to robot navigation. In: Proceedings of IEEE international conference on robotics and automation, pp 2719–2724
Doty KL, Van Aken RE (1993) Swarm robot material handling paradigm for a manufacturing workcell. In: Proceedings of the IEEE international conference on robotics and automation, vol 1, pp. 778–782
Duffie NA, Prabhu VV (1996) Heterarchical control of highly distributed manufacturing systems. Int J Comput Integr Manuf 9(4):270–281
Fleury S, Herrb M, Chatila R (1994) Design of a modular architecture for autonomous robot. In: Proceedings of the IEEE international conference on robotics and automation, pp 3508–3513
Freedman P (1991) Time, Petri nets and robotics. IEEE Trans Robot Autom 7(4):47–433
Gat E (1992) Integrating planning and reacting in a heterogeneous asynchronous architecture for controlling real-world mobile robots. In: Proceedings of the tenth national conference on artificial intelligence, pp 809–815
Liscano R, Manz A, Stuck ER, Fayek RE, Tigli JY (1995) Using a blackboard to integrate multiple activities and achieve strategic reasoning for mobile-robot navigation. IEEE Expert 10(2):24–36
Maes P (1990) Situated agents can have goals. In: Maes P (ed) Designing autonomous agents: theory and practice from biology to engineering and back. M.I.T. Press, pp 49–70
Milutinovic D, Lima P (2002) Petri net models of robotic tasks. In: Proceedings of the IEEE international conference on robotics and automation, vol 4, pp 4059–4064
Montano L, García FJ, Villarroel JL (2000) Using the time Petri net formalism for specification, validation, and code generation in robot-control applications. Int J Robot Res 19(1):59–76
Mori M (1975) The Three-eyed Beatles. Presented at the international ocean exposition, Okinawa, Japan
Mori M, Yasuda G (1973, 1974) A study on self-coordination mechanisms of systems with non-centralized neural nets 1st report, 2nd report, In: Reports of the meeting on neuro-sciences, sponsored by Ministry of Education, Science and Culture, p 177, Sep., 1973, p.168, Feb., 1974
Peterson JL (1981) Petri net theory and the modeling of systems. Prentice Hall
Murata T (1989) Petri nets: properties, analysis and applications. Proc IEEE 77:541–580
Osswald D, Martin J, Burghard C, Mikut R, Woern H, Bretthauer G (2003) Integrating a robot hand into the control system of a humanoid robot. In: Proceedings of the 2003 international conference on humanoid robots
Takai H, Mitsuoka J, Yasuda G, Tachibana K (2006) Feasibility study of sensing methods on cooperative localization for team operation of multiple mobile robots. In: Proceedings of the 3rd International conference on autonomous robots and agents, pp 393–398
Takai H, Mitsuoka J, Yasuda G, Tachibana K (2007) Cooperative workspace mapping for multi-robot team operations using ultrasonic sonar and image sensor. In: Proceedings of the 13th international conference on advanced robotics, pp 1129–1134
Takai H, Yasuda G, Tachibana K (2002) Construction of infrared wireless inter-robot communication networks for distributed sensing and cooperation of multiple autonomous mobile robots. In: Proceedings of the 15th IFAC world congress, Elsevier, pp 143–148
Wisniewski R, Barkalov A, Titarenko L Halang W (2011) Design of microprogrammed controllers to be implemented in FPGAs. Int J Appl Math Comput Sci 21(2):402–412
Yasuda G (1999) A multiagent architecture for sensor-based control of intelligent autonomous mobile robots. In: Proceedings of the 15th world congress of the international measurement confederation (IMEKO), ACTA IMEKO 1999, vol X (TC-17), pp 145–152
Yasuda G, Mori M (1971a) Application of graph theory to self-reproducing processes. In: Proceedings of the 10th SICE annual conference, in Japanese, pp 271–272
Yasuda G, Mori M (1971b) Construction of an artificial multi-molecular self-reproducing mechanism. In: Proceedings of the 14th joint automatic control conference of Japan, in Japanese, pp 65–66
Yasuda G, Mori M (1974) Future concepts on grouping robots. Presented at the meeting on neuro-sciences, sponsored by Ministry of Education, Science and Culture, Tokyo, Japan, Feb 1974
Yasuda G, Takai H (2001) Sensor-based path planning and intelligent steering control of nonholonomic mobile robots. In: Proceedings of the 27th annual conference of the IEEE industrial electronics society (IECON2001), pp 317–322
Zhu Q, Azar AT (2015) Complex system modelling and control through intelligent soft computations. Studies in fuzziness and soft computing, vol 319. Springer, Germany
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Yasuda, G. (2016). Discrete Event Behavior-Based Distributed Architecture Design for Autonomous Intelligent Control of Mobile Robots with Embedded Petri Nets. In: Azar, A., Vaidyanathan, S. (eds) Advances in Chaos Theory and Intelligent Control. Studies in Fuzziness and Soft Computing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-319-30340-6_34
Download citation
DOI: https://doi.org/10.1007/978-3-319-30340-6_34
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30338-3
Online ISBN: 978-3-319-30340-6
eBook Packages: EngineeringEngineering (R0)