Background: Reactive Robot Control

Robots, and especially mobile robots, have been one of the traditional testbeds for problem solving, planning, and other areas of artifical intelligence. As long ago as the 1960s, SRI's Shakey was used to develop and refine artificial intelligence algorithms [3]. A survey of mobile robots through the 1980s can be found in [5]; some more recent examples are in [4].

Although originally intended as a model of human problem-solving processes, rule-based systems have been used successfully in implementing reactive control strategies (ie, control strategies in which the robot exhibits behavor as reactions to events [7]) for mobile robots. The use of a rule-based system to implement a reactive strategy has been proposed in, for instance, programming NASA's Mars rover [2]. An alternative approach to implementing a reactive strategy for planetary explorers is in [1]. General information on reactive real-time systems can be found in [6].

One particular approach to a reactive robot control system is Brooks's subsumption architecture. In this control architecture, rules are divided into various levels of competence: the bottom level might simply cause a robot to move randomly; a next higher level could implement object avoidance; a level above that would implement a goal such as attempting to move toward a particular location. On every execution cycle, rules are enabled for firing based on the current robot state and sensor inputs. Of the enabled rules, a rule's level of competence determines its priority. On any given cycle, the highest-level enabled rule is fired. On most cycles, a low-level rule is fired, while relatively rarely, a higher-level rule is activated.

References

[1] Gat, E., R. Desai, R. Ivleve, J. Loch, and D. P. Miller. Behavior control for robotic exploration of planetary surfaces, in IEEE Transactions on Robotics and Automation, 10(4), pp 490-503, 1994.

[2] Harmon, S. Y. A rule-based command language for a semi-autonomous Mars rover, in Mobile Robots IV, William J. Wolfe and Wendell H. Chun, eds, pp 147-156, 1989.

[3] Hart, A.P., N. J. Nilsson, and B. Raphael, A formal basis for the heuristic determination of minimum cost paths, IEEE Transactions on Systems Science and Cybernetics

[4] Meyrowitz, A. L., Autonomous vehicles, in Proceedings of the IEEE 84(8), pp 1147-1163, 1996.

[5] Meystel, A. Autonomous Mobile Robots \(em Vehicles with Cognitive Control, World Scientific Publishing Co., 1991.

[6] Odette, L. L. Intelligent Embedded Systems, Addison-Wesley, 1991.

[7] Sowmya, A. A real-time reactive model for mobile robot architecture, in Applications of Artificial Intelligence X: Machine Vision and Robotics, Proceedings of SPIE 1708, pp 713-721, 1992.