Cooperative Target Tracking using Mobile Robots

We study the problem of multiple target tracking using multiple mobile robots. Our approach is to divide the cooperative multi-target tracking problem into two sub-problems: target tracking using a single mobile robot and on-line motion strategy design for multi-robot coordination. For single robot-based tracking, we address two key challenges: how to separate the egomotion of the robot from the motions of external objects, and how to compensate this ego-motion to detect and track moving objects robustly. An ego-motion compensation method using salient feature tracking is described, and the design of a probabilistic filter to handle the noise and uncertainty of sensor inputs is presented. The proposed method is implemented and tested in various outdoor environments using three different robot platforms: a robotic helicopter, a Segway RMP, and a Pioneer2 AT, which have unique ego-motion characteristics. For multi-robot coordination, we propose an algorithm based on treating the densities of robots and targets as properties of the environment in which they are embedded. By suitably manipulating these densities a control law for each robot is proposed. We term our approach Region-based, and describe and validate it through an example. We observe that the general approach can be significantly improved in the special case where the topology of the environment is known in advance. We derive a specialized version of the control law for this case; the resulting algorithm is called the Topological Region-Based Approach. We also give the formulation of the solution in the unstructured case, termed the Grid Region-Based Approach. These coordination approaches have been implemented in simulation, and in real robot systems. Experiments indicate that our treatment of the coordination problem based on environmental characteristics is effective and efficient. There are four additional topics we plan to address for the final thesis. First, sensor fusion techniques will be studied for target position estimation in 3D space. The current single-robot tracker integrates laser range scans into the estimation system by simply projecting the scans into the 2D image space, which causes poor estimation results when a robot turns at high velocity. Second, the stability properties of the Region-based Approach will be analyzed theoretically and through simulations. The system’s behavior in response to static or oscillating target motions will be studied. Third, the performance of the Grid Region-based Approach will be tested and