With an accurate estimate of the robot pose, robots will be capable of navigating in the environment autonomously and efficiently. In this paper, an infrastructure comprises of simultaneous camera calibration and robot localization is presented. The presented approach utilizes particle filter that integrates odometry data from robot and images captured from overhead cameras in the environment to localize the robot and calibrate overhead camera. An odometry-based motion model, HSV histogram-based measurement model and DLT (Direct Linear Transform) are designed to estimate robot poses and calibration cameras iteratively. Experiment results show the presented approach could calibrate the camera and estimate robot poses iteratively with reprojection errors around 210 mm in world reference plane.