未知环境下基于改进DWA的多机器人编队控制

Multi-robot formation control in unknown environment based on improved DWA

针对多机器人系统在未知环境下难以有效避障和保持队形的问题,在改进动态窗口法(DWA)的基础上,提出一种领航-跟随法与行为法相结合的多机器人编队控制算法.首先,通过修正速度窗口和3个现有评价函数,并添加两个新的评价函数改进DWA算法,增加速度的采样范围,提高优秀轨迹的评分,并增强机器人朝目标导航和未知环境下的全局搜索能力;然后,对周围环境和编队状态实时检测,为各机器人设计不同的行为(包括导航,避障,跟踪和等待)及其选择方式,兼顾编队避障及队形保持;接着,基于改进DWA和社会力模型(SFM)设计行为控制策略,在未知环境下使领航者能够规划适合整体编队运行的路径,跟随者能够根据编队的不同状态自适应地切换跟随方式;最后,基于Matlab和V-REP进行一系列仿真,结果表明在未知环境下,所提出的改进DWA能够显著提高机器人的通行效率和全局搜索能力,编队控制算法能够实现队形稳定保持、灵活避障与变换.

Multi-robot system may be difficult to avoid obstacles and maintain formation in the unknown environment.Based on the improvement of the dynamic window method(DWA), a multi-robot formation control algorithm combining the leader-following method and the behavior-based method is proposed. First, the original DWA is improved by modifying the speed window and three existing evaluation functions and adding two new evaluation functions. As a result, the sample range of speed is increased, the score of the better trajectory is improved, and abilities of navigation to the target and global search in unknown environment are enhanced. Second, based on the formation state and surrounding environment detected in real-time, different behaviors(navigation, obstacle avoidance, tracking and waiting) and the selection method are designed to consider both the obstacle avoidance and maintenance of the formation. Then, the control method of these behaviors is designed based on the improved DWA and social force model(SFM), so that in the unknown environment the leader can plan the path suitable for the whole formation and the follower can adaptively switch the following modes according to the different states of formation. Finally, a series of simulations based on Matlab and V-REP are carried out, whose results show that the improved DWA can significantly improve the traffic efficiency and global search ability of the robot, and the formation control algorithm can achieve the maintenance, obstacle avoidance and transformation of the formation.