Trajectory Generation for Capturing a Moving Object in Predictable Environments ∗

In the field of computer vision, it is a complex and demanding much task to detect and to track moving objects from a moving observer. However, in this paper a new scheme for a mobile robot to track and capture a moving object using images of a camera is proposed. The system consists of the following modules: data acquisition, feature extraction and visual tracking, and trajectory generation. And a single camera is used as visual sensors to capture image sequences of a moving object. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the active camera. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to capture the moving object, the linear and angular velocities are estimated and utilized. The experimental results of tracking and capturing of the target object with the mobile robot are presented.