融合沿墙行为的多移动机器人有序化多模态群集运动控制

一类基于势场原理的群集控制理论正逐步应用于多agent(智能体)/机器人稳定协同运动中.针对群集运动系统在非规则障碍物环境中运行时易出现的局部极小问题,引入基于行为的机器人学理念,构成多移动机器人多模态群集控制系统.在此框架内,仿生的动物沿端行为与有序化群集运动控制策略相融合,实现了多移动机器人系统快速聚合行为与高效避障行为的统一.移动机器人仿真实验验证了该方法的有效性.

A Multi-Mode Sequential Flocking Strategy Integrating Wall-Following Behavior for Motion Control of Multiple Mobile Robots

Flocking control is gradually attended to coordinates the motions among multiple agents or robots stably based
on potential principles. To provide a generic and efficient solution to the local minimum problem encountered within various
flocking systems in unexpected and irregular obstacle environment, a design of a multi-model flocking control for multiple
mobile robots in terms of behavior-based robotics is presented. Within this framework, animal-imitating wall-following
behavior modes are integrated with the new sequential flocking strategy. In this way, the unity of stable aggregation in
flocking and efficient obstacle avoidance motion can be efficiently and simultaneously achieved. The simulation studies are
comprehensively conducted to show the effectiveness of the proposed method.