Motion segmentation and 3D positioning of multiple mobile robots using an array of static cameras in an intelligent space

This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space. Motion segmentation and positioning are obtained from the images acquired using an array of calibrated and synchronized cameras, without previous knowledge about the number of mobile robots. These cameras are placed in fixed positions within the environment (intelligent space). The proposed algorithm does not rely on previous knowledge or invasive landmarks on board the robots. The proposal presented in this work is based on the minimization of an objective function that includes information from all the cameras. This function depends on three groups of variables: the segmentation boundaries, the 3D rigid motion parameters (linear and angular velocity components) and the depth (distance to the cameras). Before the minimization, it is necessary to initialize the segmentation boundaries and the depth. The use of an extended version of the k-means algorithm allows obtaining a good estimation of the number of robots in the scene during the initialization process. For the objective function minimization, we use a greedy iterative algorithm.