Environmental Map Generation and Egomotion Dynamic Environment for an Omnidirectional Image Sensor

Generation of a stationary environmental map i s one of the important tasks for vision based robot navigation. Under the assumption of known motion of a robot, environmental maps of a real scene can be successfilly generated by monitoring azimuth changes in a n image. Several researchers have used this property for robot navagation However, it i s difficult to observe the exact motion parameters of the robot because of encoder measurement error of the robot. Therefore, observational errors in the generated environmental map accumulate in long movements of the robot. To generate a large environmental map, i t i s desirable not t o assume known robot motion. In this paper, under the assumption of unknown translational motions of the robot, we propose a method to generate a stationary environmental map and estimate the egomotion of a robot in a dynamic environment, by using a n omnidirectional image sensor. Since both robot and objects move in the environment, the stationary map generation and the robot egomotion estimation by using a single camera are dificult because of correspondence ambiguity caused by occlusion. The proposed method can detect a moving object and find occlusion and mismatching by evaluating the estimation error of each object location.