Coverage path planning for multiple robotic agent-based inspection of an unknown 2D environment

Xudong Wang, V. Syrmos
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引用次数: 14

Abstract

This paper describes a coverage-based path planning algorithm for multiple robotic agents with the application on the automated inspection of an unknown 2D environment. The proposed path planning algorithm determines a motion path that a robotic agent will follow to sweep and survey all areas of the unknown environment, which is enclosed by the known boundary. The 2D unknown environment is decomposed into a union of simplices using the principle of Delaunay triangulation. The area coverage is equivalent to design a path for a robotic agent to follow and visit all simplices subject to certain mission constraints. A hierarchical mission planner is designed to allocate mission tasks among multiple agents in each level and pass information down to the next level along the hierarchy. The proposed path planning algorithm has been tested and evaluated on the problem of planning path for two types of robotic agents - flying agents and crawling agents in a two-tier hierarchical mission planner to cover various unknown 2D environments.
基于多机器人代理的未知二维环境检测覆盖路径规划
本文描述了一种基于覆盖的多机器人智能体路径规划算法,并将其应用于未知二维环境的自动检测。提出的路径规划算法确定了机器人代理将遵循的运动路径,以扫描和调查未知环境中被已知边界包围的所有区域。利用Delaunay三角剖分原理,将二维未知环境分解为简并。区域覆盖相当于设计一条路径,让机器人代理在一定的任务约束下遵循并访问所有的简单体。分层任务规划器的目的是在每一层的多个agent之间分配任务,并沿着层次结构向下传递信息到下一层。本文提出的路径规划算法在两层分层任务规划器中对飞行和爬行两种机器人智能体的路径规划问题进行了测试和评估,以覆盖各种未知的二维环境。
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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