Motion Estimation of a Mobile Robot Using Different Types of 3D Sensors

Motion estimation is one of the most important tasks for autonomous mobile robots. Modern mobile robots are equipped with different types of visual sensors that can provide wide ranges of outputs which can be used as reliable inputs for the computing of the robots displacement. One of the widely used visual sensors on mobile robots is the stereo camera due to its simplicity and availability. However, the recently invented Photonic Mixer Device (PMD) that uses the time of flight principle, also becomes more and more popular because of its robustness against ambient light and weak textured surfaces. This paper introduces the compared results of the motion estimation using two different types of 3D sensors (stereo and PMD) and also suggests a new approach to fuse their data in order to improve the calculation accuracy. An experiment was conducted using a mobile robot where the motion of the robot was evaluated using a least square technique. The results from each sensor were obtained and compared to prove their capability toward the motion estimation task.