基于pso的未知环境下多机器人协同觅食方法

Yifan Cai, Simon X. Yang, G. Mittal
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引用次数: 6

摘要

未知环境下的协同觅食任务是机器人技术的重要组成部分,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。本文提出了一种改进的基于势场(potential field-based, IPPSO)的协作机器人在未知环境中完成觅食任务的方法。提出了一种多机器人系统的协作策略,利用势场函数作为粒子群算法的适应度函数。在模拟研究中,研究了各种场景。仿真研究证明了该方法的有效性。
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 to cooperative foraging multi-robots in unknown environments
Cooperative foraging tasks in unknown environments are fundamentally important in robotics, where the real-time path planning and proper task allocation strategies are desirable for multi-robot cooperation. In this paper, an improved potential field-based (IPPSO) approach is proposed for cooperative robots to accomplish the foraging 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. In the simulation studies, various scenarios are investigated. The effectiveness of the proposed approach is demonstrated by simulation studies.
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