Abstract：The colony of autonomous micro mobile robot will run in some unknown and unstructured environment. There are many limits to autonomous micro mobile robot. These limits make the robot only know the part information about the environment and the robot can’t remember many past statements. So it is very difficult to design the autonomous robot based on information. It is also difficult to ensure the robot behavior is very validity to its environment and its task when we design the autonomous micro mobile robot based on behavior. This paper presents a gene algorithm based on behavior. We design three kinds of base behavior: Obstacle-avoidance behavior, fault-repair behavior, and fault-scout behavior. At the beginning of the gene algorithm,the coders of these behavior are produced at random. At the last the behavior of the colony and the robot are very good to the environment and the task when the colony runs in the simulation environment. The result shows this method is very validity.
 Brooks R A. A Robust Layered Control System for A Mobile Robot. IEEE Journal of Robotics and Automation, 1986, RA-2(1)  Marco Colombetti, Marco Dorigo. Training Agents To Perform Sequential Behavio r. Adaptive Behavior, Mit Press, 1994,2(3)  Marco Dorigo, Uwe Schnepf. Genetics-Based Machine Learning and Behavior Base d Robotics: A New Synthesis. IEEE Transactions on Systems, Man, and Cybernetics, 1993,23(1): 141-154  Hyo-Byung Jun, Kwee-Bo Sim. Behavior Learning and Evolution of Collective A utonomous Mobile Robots Based on Reinforcement Learning and Distributed Genetic Algorithms. IEEE International Workshop On Robot and Human Communication, 1997 : 248-253  李人厚编著.智能控制理论和方法.西安电子科技大学出版社.1999年10月