A Hierarchical Coverage Path Planning Algorithm for Unknown Environments

2026-09-11

AI Summary

本文提出了一种用于未知环境的在线覆盖路径规划算法，通过逐步分解搜索区域并使用层次分解树来组织子区域，以提高覆盖效率。

Abstract

This paper presents an online coverage path planning algorithm for unknown environments. During navigation, the initially unknown search area is progressively decomposed into disconnected subareas as new obstacle information is acquired and coverage proceeds. These subareas are organized in an incrementally constructed decomposition tree that preserves their hierarchical parent-child relationships. Based on this tree, a global coverage tour is maintained and updated online by prioritizing newly generated child subareas according to their exploration states and distances from the robot. A local planner then generates coverage motions within each selected subarea, allowing the robot to adapt its trajectory as the environment is gradually revealed. Its performance is evaluated via high-fidelity simulations in complex scenarios. The results show improved coverage efficiency in terms of path length and overlap ratio in comparison to three baseline algorithms.

Problem

• coverage path planning
• unknown environments
• decomposition tree
• exploration states

Innovation

• online coverage path planning
• hierarchical decomposition
• decomposition tree
• exploration state prioritization
• adaptive trajectory