Behavioral speed control based on tactical information

This paper presents a novel organization of reactive behaviors which avoids the problems generally associated with arbitration or combination of behaviors. The organization uses tactical behaviors to attempt to safely satisfy the intent of strategic behaviors given the immediate situation (e.g., state of the environment, status of the robot, certainty, etc.) A tactical speed control behavior using fuzzy logic is described in detail. Experiments with a nonholonomic mobile robot navigating a 150 ft course show that a tactical speed control behavior improves navigational performance without requiring either knowledge about the strategic behavior (follow-line) or the complexity of the course. The speed control behavior has also been used in conjunction with shared control and has been transferred to a holonomic robot, demonstrating how the behavioral organization enhances software modularity and portability.

[1]  François G. Pin,et al.  Using Custom-designed Vlsi Fuzzy Inferencing Chips For The Autonomous Navigation Of A Mobile Robot , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Robin R. Murphy,et al.  Lessons learned in integrating sensing into autonomous mobile robot architectures , 1997, J. Exp. Theor. Artif. Intell..

[3]  Charles E. Thorpe,et al.  Combining multiple goals in a behavior-based architecture , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[4]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[5]  John Yen,et al.  A fuzzy logic based extension to Payton and Rosenblatt's command fusion method for mobile robot navigation , 1995, IEEE Trans. Syst. Man Cybern..

[6]  Takayuki Tanaka,et al.  Intelligent fuzzy motion control of mobile robot for service use , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[7]  J. Fei,et al.  The analysis of fuzzy knowledge-based systems using cell-to-cell mapping , 1990, Proceedings. 5th IEEE International Symposium on Intelligent Control 1990.

[8]  François G. Pin,et al.  Using fuzzy behaviors for the outdoor navigation of a car with low-resolution sensors , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[9]  Ronald C. Arkin,et al.  Motor schema based navigation for a mobile robot: An approach to programming by behavior , 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.