障碍环境下多移动机器人动态优化队形变换

Dynamic and Optimized Formation Switching for Multiple Mobile Robots in Obstacle Environments

针对未知障碍环境下的地面多移动机器人,提出了在线的动态优化队形变换避障策略.该策略首先针对编队控制中常用的队形形状建立了队形知识库,同时充分考虑环境约束,设计了包含队形零变换、同构变换和异构变换3种模式的编队避障策略.其中,队形同构变换模式通过引入伸缩因子,在没有破坏原有队形结构的基础上实现了队形大小的缩放;队形异构变换模式下,在定义了包含队形失真度、能量消耗率和队形变换收敛时间比等性能指标的基础上,通过领航机器人获得的环境信息和当前的队形形状,对提出的环境适应度函数进行优化求解获得最佳的leader-follower拓扑结构.最终,不同场景下的大量仿真实验验证了本文方法切实有效.

An online dynamic and optimized formation switching strategy is proposed for obstacle avoidance of multiple ground mobile robots in unknown obstacle environments. A formation knowledge base is built according to common forma- tion shapes in formation control, and a formation obstacle-avoiding strategy including none formation switching, isomorphic formation switching and isomeric formation switching is deigned, in which environment constraints are taken into consider- ation fully. In the isomorphic formation switching mode, the formation can be contracted or expanded in size by changing the dilation factor while preserving the shape. In the isomeric formation switching mode, performance indices including formation distortion degree, energy consumption ratio and formation change convergence ratio are established. On basis of the indices, environment information detected by the leader robot and current formation shape, the optimal leader-follower topology structure is obtained by optimizing the proposed environment fitness function. Finally, simulation experiments in various environments are carried out to demonstrate that the proposed strategy is feasible and effective.