3D Environment Modeling And Autonomous Motion Planning For Mobile Robot

The effective recognition and perception of 3D environment are the most fundamental problems that have to be solved before the mobile robot can navigate and explore autonomously in complex outdoor environment. Compared with the indoor environment, the outdoor environment with completely unstructured characteristics has put forward higher requirements for 3D environment modeling and reconstruction as well as motion planning.This study focuses on 3D environment modeling and autonomous motion planning of unstructured scene, which aims to build a mobile robot intelligent control system with real time modeling and reconstruction ability as well as real time motion planning and decision-making function.For the laser range data acquired from 3D ranging system, different methods are applied to implement the modeling of unstructured scene in this thesis, which include line extraction, plane extraction and 3D map building et al. Two different methods are proposed to implement plane segmentation. In the area-expending algorithm, we solve the smooth-gradient problem effectively according to the angle between normal vectors.Based on the environment model, two different autonomous motion planning methods are proposed: motion planning based on geometry-altitude model and motion planning based on terrain evaluation. In the former method, we synthesize geometry model and elevation model to build a 3D road map, then acquire final path to meet the security require using Dijkstra algorithm, this method overcome their respective disadvantages of the two models effectively and enable the validity and rationality of the final path. In the latter method, we distribute the laser range data into horizontal grids, and make terrain evaluation according to the distribution of the laser range data in and between grids. During motion planning, the whole scene is divided into different area with corresponding traversable value, and then a motion planning method is proposed which has the advantage of meeting multiple goals and being adaptive to different situation. The experiment results show the validity and robustness of these motion planning methods.