Multiple Objective vs. Fuzzy Behavior Coordination
In the behavior-based paradigm [4,16], the control of a robot is shared between a set of purposive processes, called behaviors. Based on selective sensory in-formation, each behavior produces/proposes reactions to control the robot with respect to a particular objective, i.e., a narrow aspect of the robot’s overall task. Behaviors with different and possibly incommensurable objec-tives may produce conflicting actions that are seemingly irreconcilable. Thus, the design of effective behavior coordination mechanisms is a major research issue.
KeywordsMobile Robot Action Selection Fuzzy Approach Discrete Event System Behavior Coordination
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- 2.Ronald C. Arkin. Towards the Unification of Navigational Planning and Reactive Control. AAAI Spring Symposium on Robot Navigation, March 1989.Google Scholar
- 4.Ronald C. Arkin. Behavior-Based Robotics. Intelligent Robotics and Autonomous Agents series. MIT Press, May 1998.Google Scholar
- 5.Rodney A. Brooks. A Robust Layered Control System for a Mobile Robot. IEEE Journal of Robotics and Automation, 2(l):14–23, March 1986.Google Scholar
- 6.Vira Chankong and Yacov Y. Haimes. Multiobjective Decision Making - Theory and Methodology, volume 8. North-Holland, 1983.Google Scholar
- 8.Joel Hoff and George Bekey. An Architecture for Behavior Coordination Learning. In IEEE International Conference on Neural Networks, Perth, Australia, volume 5, pages 2375–2380, November 1995.Google Scholar
- 9.Peter G. W. Keen. The Evolving Concept of Optimality. In Martin K. Starr and Milan Zeleny, editors, Multiple Criteria Decision Making, volume 6 of Studies in the management sceiences, pages 31–57. North-Holland Publishing Company, 1977.Google Scholar
- 11.Kurt Konolige. Saphira Software Manual. ActivMedia Inc., version 6.1 edition, 1998.Google Scholar
- 12.Jana Kosecka and Ruzena Bajcsy. Discrete Event Systems for Autonomous Mobile Agents. Proceedings Intelligent Robotic Systems ’93 Zakopane, pages 21–31, July 1993.Google Scholar
- 13.Steen Kristensen. Sensor Planning with Bayesian Decision Theory. Technical Report, Laboratory of Image Analysis, Aalborg University, June 1995.Google Scholar
- 14.Edward W. Large, Henrik I. Christensen, and Ruzena Bajcsy. Scaling the Dynamic Approach to Path Planning and Control: Competition among Behavioral Constraints. International Journal of Robotics Research, 18:37–58, January 1997.Google Scholar
- 15.Pattie Maes. How To Do the Right Thing. Technical Report NE 43–836, AI-Laboratory, Massachusetts Institute of Technology, 545 Technology Square, Cambridge, MA 02139, USA, 1989.Google Scholar
- 16.Maja Mataric. Behavior-Based Control: Examples from Navigation, Learning, and Group Behavior. Journal of Experimental and Theoretical Artificial Intelligence, special issue on Software Architectures for Physical Agents, 9(2–3):323–336, 1997.Google Scholar
- 17.David W. Payton. Internalized plans: A representation for action resources. In Pattie Maes, editor, Designing Autonomous Agents, pages 89–104. MIT/Elsevier, The MIT Press, Cambridge, Massachusetts, London, England, 1990.Google Scholar
- 19.F. G. Pin and Y. Watanabe. Automatic Generation of Fuzzy Rules Using the Fuzzy Behaviorist Approach: The Case of Sensor-Based Robot Navigation. Intelligent Automation and Soft Computing, 1(2): 161–178, 1995.Google Scholar
- 20.Paolo Pirjanian. Multiple Objective Action Selection & Behavior Fusion using Voting. PhD thesis, Department of Medical Informatics and Image Analysis, Institute of Electronic Systems, Aalborg University, Fredrik Bajers Vej 7, DK-9220 Aalborg, Denmark, August 1998. http://www-robotics.usc.edu/”paolo/publications.Google Scholar
- 21.Paolo Pirjanian. Multiple objective action selection in behavior-based control. In The proceedings of the 6th Symposium for Intelligent Robotic Systems, Edinburgh, Scotland, pages 83–92, July 1998.Google Scholar
- 22.Paolo Pirjanian. Satisficing action selection. In Sensor Fusion and Decentralized Control in Robotic Systems, volume 3523, pages 157–168. SPIE Conference, November 1998.Google Scholar
- 23.Paolo Pirjanian. Behavior coordination mechanisms - state-of-the-art. Technical Report IRIS-99–375, Institute of Robotics and Intelligent Systems, School of Engineering, University of Southern California, October 1999. http://iris.usc.edu/~irislib.
- 24.Jukka Riekki and Juha Roning. Reactive Task Execution by Combining Action Maps. In International Conference on Integrated Robots and Systems (IROS), pages 224–230, Grenoble, France, September 1997.Google Scholar
- 25.Julio K. Rosenblatt. DAMN: A Distributed Architecture for Mobile Navigation. In AAAI Spring Symposium on Lessons Learned from Implemented Software Architectures for Physical Agents, Stanford, CA. AAAI Press, Menlo Park, CA., March 1995.Google Scholar
- 26.Enrique H. Ruspini. On truth and utility. In R. Kruse and P. Siege, editors, Symbolic and Quantitative Approaches to Uncertainty, pages 297–304. Springer-Verlag, 1991.Google Scholar
- 27.Alessandro Saffiotti. Using Fuzzy Logic in Autonomous Robot Navigation: a catalogue raisonne. Soft Computing 1(4), 1997. Online at http://www.aass.oru.se/Living/FLAR/.
- 30.Eddie Tunstel. Coordination of Distributed Fuzzy Behaviors in Mobile Robot Control. In IEEE International Conference on Systems, Man,and Cybernetics, pages 4009–4014, Vancouver, BC, Canada, October 1995.Google Scholar