Motion Detection and Object Tracking for an AIBO Robot Soccer Player

Movement analysis is a fundamental ability for any kind of robot. It is especially important for determining and understanding the dynamics of the robot’s surrounding environment. In the case of robot soccer players, movement analysis is employed for determining the trajectory of relevant objects (ball, teammates, etc.). However, most of the existing movement analysis methods require the use of a fixed camera (no movement of the camera while analyzing the movement of objects). As an example, the popular background subtraction algorithm employs a fixed background for determining the foreground pixels by subtracting the current frame with the background model. The requirement of a fixed camera restricts the real-time analysis that a soccer player can carry out. For instance, a human soccer player very often requires the determination of the ball trajectory when he is moving himself, or when he is moving his head, for making or planning a soccer-play. If a robot soccer player should have a similar functionality, then it requires an algorithm for real-time movement analysis that can perform well when the camera is moving. The aim of this work is to propose such an algorithm for an AIBO robot. This algorithm can be adapted for almost any kind of mobile robot. The rationale behind our algorithm is to compensate in software the camera movement using the information about the robot body and robot head movements. This information is used to correctly align the current frame and the background. In this way, a stabilized background is obtained, although the camera is always moving. Afterward, different traditional movement analysis algorithms can be applied over the stabilized background. Another feature of our algorithm is the use of a Kalman Filter for the robust tracking of the moving objects. This allows to have reliable detections and to deal with common situations such as double detections or no detection in some frames because of variable lighting conditions. This chapter is organized as follows. In section 2 we present some related work. In section 3 is described the here proposed motion analysis algorithm for AIBO robots. Experiments