Robot Coverage Path Planning for General Surfaces Using Quadratic Differentials
This addresses the problem of efficient robot exploration on complex surfaces for robotics applications, presenting a novel method for a known bottleneck.
The paper tackles robot coverage path planning on general surfaces by using holomorphic quadratic differentials for intrinsic parametrization, resulting in natural and efficient robot paths that minimize duplicate coverage.
Robot Coverage Path planning (i.e., provide full coverage of a given domain by one or multiple robots) is a classical problem in the field of robotics and motion planning. The goal is to provide nearly full coverage while also minimize duplicately visited area. In this paper we focus on the scenario of path planning on general surfaces including planar domains with complex topology, complex terrain or general surface in 3D space. The main idea is to adopt a natural, intrinsic and global parametrization of the surface for robot path planning, namely the holomorphic quadratic differentials. Except for a small number of zero points (singularities), each point on the surface is given a uv-coordinates naturally represented by a complex number. We show that natural, efficient robot paths can be obtained by using such coordinate systems. The method is based on intrinsic geometry and thus can be adapted to general surface exploration in 3D.