An adaptive coverage path planning method considering energy constraints

S. Shao
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Abstract

Coverage path planning algorithms are widely used by many robots conducting work like floor sweeping, map generating and underwater searching. One of the practical methods is the Backtracking Spiral Algorithm (BSA), which is efficient and complete coverage guaranteed. In practice, however, autonomous robots are faced with the problem of energy constraints. The duration of the battery of a robot is usually limited. This paper presents an adaptive coverage path planning method based on BSA considering the energy constraints. The objective of this method is to minimise the total length of the path the robot travelled to recharge while guaranteeing complete coverage. This method uses an estimation strategy which would use the energy consumption of the last round as a conjecture of that of the next round and recharge when the remaining energy would probably be insufficient to complete the next round while the robot passes nearby the recharging station. A simulation result is then provided to serve as proof of this method.
考虑能量约束的自适应覆盖路径规划方法
覆盖路径规划算法被广泛应用于许多机器人进行扫地、地图生成和水下搜索等工作。其中一种实用的方法是回溯螺旋算法(Backtracking Spiral Algorithm, BSA),它是一种高效且保证全覆盖的算法。然而,在实践中,自主机器人面临着能量限制的问题。机器人电池的持续时间通常是有限的。提出了一种考虑能量约束的基于BSA的自适应覆盖路径规划方法。这种方法的目标是在保证完全覆盖的情况下,最小化机器人充电路径的总长度。该方法采用了一种估计策略,将上一轮的能量消耗作为下一轮能量消耗的推测,当机器人经过充电站附近时,剩余能量可能不足以完成下一轮的能量消耗时进行充电。仿真结果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。
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