未知环境下协同多机器人模糊避障方法研究

Yifan Cai, Simon X. Yang
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引用次数: 18

摘要

未知环境下的协同探索在机器人技术中具有重要意义,多机器人协作需要实时的路径规划和合理的任务分配策略。本文提出了一种基于粒子群算法的协作机器人在未知环境中完成目标搜索任务的方法,并结合模糊避障模块。提出的多机器人系统协作策略利用势场函数作为粒子群算法的适应度函数,提出的模糊避障方法可以提高机器人的轨迹平滑度。在仿真研究中,研究了各种场景,并与无模糊规则的方法进行了比较。仿真和对比研究验证了该方法的有效性,提高了机器人的轨迹平滑度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A PSO-based approach with fuzzy obstacle avoidance for cooperative multi-robots in unknown environments
Cooperative exploration in unknown environments is fundamentally important in robotics, where the realtime path planning and proper task allocation strategies are desirable for multi-robot cooperation. In this paper, a PSO-based approach, combined with a fuzzy obstacle avoidance module, is proposed for cooperative robots to accomplish the target searching tasks in unknown environments. The proposed cooperation strategy for a multi-robot system makes use of the potential field function as the fitness function of PSO, while the proposed fuzzy obstacle-avoidance method can improve the robot trajectory smoothness. In the simulation studies, various scenarios are investigated and compared to the method without fuzzy rules. The effectiveness of the proposed approach and the robot trajectory smoothness improvement are demonstrated by simulation and comparison studies.
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