自主机器人视觉与行为模型及避障研究

主动的障碍物探测与避障行为控制一直是自主机器人的重点研究课题.在以往的研究中,机器人的视觉系统与电动机驱动系统往往是各自独立的构成控制体系,人们很少关注它们之间的关系,这样就从本质上割裂了两者之间的紧密耦合关系,减少了获取更多信息的途径.本文主要研究如何建立机器人视觉与电动机驱动系统关系的视觉与行为模型,通过这种紧密的耦合关系为机器人运动提供更丰富的信息来源.此外,在该模型的基础上引入了强化学习,引导机器人进行动态避障.实验表明该方法是可靠的,能够满足实时性要求.

Research on Vision-Action Model of Autonomous Robot and Obstacle Avoiding

Active obstacle detecting and avoiding for autonomous robot are significant research fields.In the past,the vision system and motor controlling system of the robot have been developed independently.Most people ignored the relationship of these two systems,separated the close coupling,and reduced the ways to obtain more information.Here,a Vision-Action model is developed to describe the relationship between the robot vision and motor action,in which the coupling provides more information resources of the environment.In addition,reinforced learning is used for autonomous robot to avoid the dynamic obstacle based on this Vision-Action model.Our experiments in the method were carried out stably and in real time.