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Multi-robot path-planning using artificial bee colony optimization algorithm

机译:基于人工蜂群优化算法的多机器人路径规划

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Path-planning is an interesting problem in mobile robotics. This paper proposes an alternative approach to path-planning of mobile robots using the artificial bee colony (ABC) optimization algorithm. The problem undertaken here attempts to determine the trajectory of motion of the robots from predefined starting positions to fixed goal positions in the world map with an ultimate objective to minimize the path length of all the robots. A local trajectory planning scheme has been developed with ABC optimization algorithm to optimally obtain the next positions of all the robots in the world map from their current positions, so that the paths to be developed locally for n-robots are sufficiently small with minimum spacing with the obstacles, if any, in the world map. Experiments reveal that the proposed optimization scheme outperforms two well-known algorithms with respect to standard metrics, called average total path deviation and average uncovered target distance.
机译:路径规划是移动机器人技术中一个有趣的问题。本文提出了一种使用人工蜂群(ABC)优化算法进行移动机器人路径规划的替代方法。此处出现的问题试图确定机器人在世界地图中从预定的起始位置到固定的目标位置的运动轨迹,并最终目标是最小化所有机器人的路径长度。已经开发了具有ABC优化算法的局部轨迹规划方案,以从其当前位置最佳地获取世界地图上所有机器人的下一个位置,从而使n机器人在本地开发的路径足够小,并且具有最小的间距世界地图中的障碍物(如果有)。实验表明,就标准指标而言,所提出的优化方案优于两种众所周知的算法,即平均总路径偏差和平均未发现目标距离。

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