自主式微小型移动机器人的自动避障行为研究

针对多微小型移动机器人工作环境的模型未知或不确定，以及该机器人本身 的某些限制，采用基于行为的研究方法，实现了自行设计的自主式微小型移动机器人在未知 、动态环境中的自动避障，设计了该机器人的障碍物回避行为，采用了电机神经元网络选择 机器人的自动避障动作，并用增强式学习的动作评判结果在线修改网络的权值，结合机器人 的漫步行为，采用机器人的安全漫步任务验证了该方法的有效性．

RESEARCH ON AUTOMATIC AVOID-OBSTACLE BEHAVIOR FOR AUTONOMOUS MICRO MOBILE ROBOTS

Because of uncertainties of the environment and the robot mathematic model and some limits of these robots, it is difficult for autonomous micro mobile robots to avoid obstacle. In this paper, we design an automatic avoid-obstacle avodance behavior. This behavior uses the artificial motor neuron network to select its moving mode and uses reinforcement learning to adjust the weight of the network at real time. The results of the safe wander are made of wander behavior, and automatic obstacle avoidance behavior have shown its validity.