Distributed formation control with pose estimation in multi-robot systems

Distributed-formation control is motivated by many applications of multi-robot systems. Many existing control algorithms assume that each robot is equipped with sophisticated sensors that can measure robot´s pose, i.e., position and orientation. In this paper, however, we consider that each robot has only ranging sensors (such as ultrasonic ones) and coarse positioning sensors (such as GPS). We apply continuous-time extended Kalman filter (CEKF) to estimate the robot´s pose. By exploiting the collaboration with the neighboring robots, a virtual structure based distributed algorithm is adopted for achieving global-formation. We evaluate the impact of neighborhood size on the control performance by extensive simulations. Moreover, we set up a platform and conduct experiments for different scenarios to verify the proposed algorithms.