Automatic calibration and trajectory reconstruction of mobile robot in camera sensor network

To operate mobile robots in an intelligent space such as a distributed camera sensor network, pre-calibration of all environmental cameras (i.e., determining the absolute poses of each camera) is an essential task that is extremely tedious. The optimization problem for camera calibration with a mobile robot has been intensively studied in the past. However, most existing solutions have limitations in that they can estimate only three degree of freedom (DOF) parameters (x, y, yaw) with restrictive assumptions. In this paper, we propose a novel method that achieves trajectory reconstruction of a mobile robot and calibration of complete 6DOF (x, y, z, roll, pitch, yaw) external parameters of distributed cameras by utilizing easily obtainable grid map information of the environment as prior information. In addition, a novel two-way observation model is proposed. The map information and two-way observation model help seek a global minimum solution (i.e., 6DOF camera parameters and robot trajectory) within the objective function containing many local minimums. We evaluate the proposed method in a simulation environment with a virtual camera network of up to 10 cameras and a real environment with a mobile robot in a wireless camera network The results demonstrate that the proposed framework can estimate the 6DOF camera parameters and the target trajectory successfully.