Motion Planning Strategies for Autonomously Mapping 3D Structures

Abstract

This paper presents a system capable of autonomously mapping the visible part of a bounded three-dimensional structure using a mobile ground robot equipped with a depth sensor. We describe motion planning strategies to determine appropriate successive viewpoints and attempt to fill holes automatically in a point cloud produced by the sensing and perception layer. We develop a local motion planner using potential fields to maintain a desired distance from the structure. The emphasis is on accurately reconstructing a 3D model of a structure of moderate size rather than mapping large open environments, with applications for example in architecture, construction and inspection. The proposed algorithms do not require any initialization in the form of a mesh model or a bounding box. We compare via simulations the performance of our policies to the classic frontier based exploration algorithm. We illustrate the efficacy of our approach for different structure sizes, levels of localization accuracy and range of the depth sensor.