Multi-model motion tracking under multiple team member actuators

Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on the object to be tracked, as the motion can become highly discontinuous and nonlinear. We have previously developed a successful tracking approach that switches among target motion models as a function of one robot's actions. In this paper, we consider the object to be effected by a team of agents. We contribute on our team-based tracking method that can use a dynamic multi-motion model based on a team coordination plan. We present the multi-target multi-model probabilistic tracking algorithm in detail and present empirical results both in simulation and in a human-robot Segway soccer team. The team coordination plan allows the robot to much more effectively track mobile targets.

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