动态环境下移动机器人避障策略研究

Research on Obstacle Avoidance Strategy of Mobile Robot in Dynamic Environment

【目的】分析动态环境下移动机器人避障技术,从而实现有效的动态避障及新技术应用。【方法】以移动机器人为研究对象,对人工势场法、避障控制法、人工神经网络避障控制法、快速扩展随机树算法等避障策略进行分析,在此基础上对人工势场法避障策略进行改进。【结果】解决路径规划对象徘徊于局部极小值点的问题。当移动机器人抵达局部极小处时,在新势场作用下,会摆脱局部极小点束缚,能有效解决目标点不可达的问题。【结论】通过弥补人工势场法来解决路径规划过程中缺少全局信息的缺陷,使移动机器人在未知、动态、复杂的环境中行进,有针对性地增加数个虚拟目标点,在不过多增加计算量的前提下,能有效提高移动机器人在避障过程使用人工势场法的适用性。

[Purposes]This paper aims to analyze the obstacle avoidance technology of mobile robot in dynamic environment,so as to realize effective dynamic obstacle avoidance and new technology application.[Methods] Taking the mobile robot as the research object,the artificial potential field method,obstacle avoidance control method,artificial neural network obstacle avoidance control method and fast extended random tree algorithm and other strategies were analyzed,on this basis the obstacle avoidance strategy of artificial potential field method was improved.[Findings] The problem that the path planning object wanders around the local minimum point is solved.When the mobile robot reaches the local minimum,under the action of the new potential field,it will get rid of the constraint of the local minimum point,which can effectively solve the problem that the target point is not reachable.[Conclusions] By making up for the lack of global information in the path planning process by the artificial potential field method,the mobile robot can move in an unknown,dynamic and complex environment,and increase several virtual target points in a targeted manner.On the premise of not increasing the amount of calculation,it can effectively improve the applicability of the artificial potential field method used by the mobile robot in the obstacle avoidance process.