Depthmap-based obstacle avoidance on rough terrain

Abstract

It is an important and difficult task for a mobile robot to detect the maneuverable area and to avoid obstacles. Numerous methods using ultra sonic or infrared sensors have been successfully proposed and adapted to various robots. These robots, however, cannot move around in unleveled areas because their sensors are incapable of measuring in a three-dimensional (3D) environment. Some obstacle avoidance methods using 3D sensors were proposed. It is a problem to move the robot around smoothly and continuously, considering that these methods require numerous processing steps and time to determine the obstacles and the avoidance path. In this paper, a new obstacle avoidance method using a depthmap is proposed that applies 3D sensor technology to autonomous exterior robot systems. Employing this method the robot is able to recognize the obstacle continuously and thus can be used on rough terrain. All processes in the algorithm handle images without the environmental model. In recent years, a sensing device used for laser modules or CCD cameras that can sense 3D space in real-time have been developed. Using such a sensor in conjunction with the proposed method, the test unit and autonomous vehicle were built to evaluate the methodology in an outdoor environment These units were able to detect the obstacle, avoid it, and Iocomote autonomously on rough terrain. As a result, this method has the advantage of robustness on rough terrain, and an autonomous mobile robot with this test unit is capable of navigation on an unleveled road.