In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.