In this paper, we propose a dynamic visual servo controller for precise tracking of robot manipulator. For the controller, we used a dual-loop structure which includes a vision controller and dynamic controller with different sampling speed. The vision controller is accommodated in the outer control loop with the aid of eye-in-hand camera, implementing the image based visual servoing method. As an inner loop controller, an adaptive backstepping controller is derived for position control of joint angle together with PID controller. The performance of proposed visual servo controller has been verified through computer simulation with V-REP simulation package.

This paper proposes a new SLAM (Simultaneous Localization and Mapping) algorithm based on hybrid map method. We express the environment surrounding mobile robot with a grid and a feature map. Using the reliability of estimation for individual map, we calculate the importance factor for Rao-Blackwellized Particle Filter (RBPF) resampling. In this way, we improve the accuracy of the algorithm and reduce computational complexity. Experimental results verify the feasibility and effectiveness of our algorithm.