计算机科学
路径(计算)
运动规划
任意角度路径规划
图形
算法
规划师
基线(sea)
机器人
高效算法
数学优化
图论
数据挖掘
算法设计
计算复杂性理论
实时计算
分层数据库模型
移动机器人
作者
Zongyuan Shen,Burhanuddin Shirose,Prasanna Sriganesh,Matthew Travers
标识
DOI:10.1109/iros60139.2025.11247648
摘要
Efficient coverage of unknown environments requires robots to adapt their paths in real time based on on-board sensor data. In this paper, we introduce CAP, a connectivity-aware hierarchical coverage path planning algorithm for efficient coverage of unknown environments. During online operation, CAP incrementally constructs a coverage guidance graph to capture essential information about the environment. Based on the updated graph, the hierarchical planner determines an efficient path to maximize global coverage efficiency and minimize local coverage time. The performance of CAP is evaluated and compared with five baseline algorithms through high-fidelity simulations as well as robot experiments. Our results show that CAP yields significant improvements in coverage time, path length, and path overlap ratio.
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