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Local Path Planning for Autonomous Mobile Robot Based on APF-BUG Algorithm with Ground Quality Indicator

机译：基于APF-BUG算法的自主移动机器人基于地面质量指示器的本地路径规划

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In this paper, an enhanced Artificial Potential Field (AFP) algorithm applied to autonomous mobile robot is presented. The proposed solution is extended by an additional BUG algorithm and a ground quality indicator. The modification allows to avoid local minima in path planning caused by complex terrain obstacles. The developed algorithm takes into account the substrate quality, classifying a poor ground as an obstacle. It was implemented and tested in Matlab software, utilizing the track planning algorithm as a state machine. The simulation environment enables graphical presentation of the chosen path and the arrangement of moving area. The article presents and discusses a basic issue in local path planning of autonomous mobile platforms, i.e. the ground quality, which is ignored in classical algorithms. This is a non-trivial problem, which impacts the success rate of getting the final destination. The developed algorithm is extended by a BUG rule and ground quality indicator which allows to avoid immobilization of the platform.
机译：本文介绍了应用于自主移动机器人的增强的人工势域（AFP）算法。所提出的解决方案通过额外的错误算法和地面质量指示器进行扩展。该修改允许避免由复杂地形障碍物引起的路径规划中的局​​部最小值。开发的算法考虑了基板质量，将差的地面分类为障碍物。它在Matlab软件中实现和测试，利用轨道规划算法作为状态机。仿真环境使得能够的图形呈现所选择的路径和移动区域的布置。本文提出并讨论了自主移动平台的本地路径规划的基本问题，即地面质量，在经典算法中被忽略。这是一个非琐碎的问题，它会影响最终目的地的成功率。发达的算法由BUG规则和地面质量指示灯延伸，允许避免对平台固定的固定。

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