智能扫地机器人全覆盖路径规划

Bing Luo, Yu-Chao Huang, Fuqin Deng, Weike Li, Yongsuo Yan
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引用次数: 5

摘要

全覆盖路径规划作为自动控制中的通用优化问题,是智能扫地机器人的有用功能之一,它使扫地机器人更快、更高效地完成扫地。传统的单元分解方法虽然得到了解,但对于复杂凹多边形环境的过度分解和忽略转弯会降低优化效果。针对扫地机器人的实际应用,提出了三个方面的改进,即在代价函数中加入转弯代价,保留凹区可与相邻区域合并规划而不分解,通过穷举搜索和蚁群算法考虑单元路径的全局规划,并考虑单元间的转移,从而可以更好地应用于整个复杂环境。仿真实验结果表明,该方法可以有效地减少转弯和总成本,使扫地机器人更有效地完成覆盖。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Complete Coverage Path Planning for Intelligent Sweeping Robot
As a universal optimization problem in automatic control, complete coverage path planning is one of the useful functions for intelligent sweeping robot, which makes sweeping robot complete sweeping more quickly and efficiently. Though conventional unit decomposition method has got solution, excessive decomposition for complex concave polygon environment and ignoring turning degrade the optimization effect. Considering the practical application of sweeping robot, improvements in three aspects are proposed that the cost function is added with the cost of turning, concave areas which can be combined planning with adjacent area are retained no decomposition, and global planning of unit path with transfer between units are considered by exhaustive search and ant colony algorithm, which can be applied to whole complex environment with better performance. Simulation experimental results show that the proposed approach can effectively reduce turning and total cost, make sweeping robot complete coverage more effectively.
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