In recent years, the diversity and applications of robots are considerably growing and the development of technology provides new facilities to employ the robots more and better. Single-robot systems are not the best way in all applications of robots. Growing range of issues and problems that will exist in the future will bring potential benefits of multi-robot systems. For instance, search and rescue problem, mapping of hazardous and hostile environments, target searching and tracking, space and submarine explorations are the missions that the multi-robot systems will be utilized to execute them. However utilizing a group of robots to implement the tasks needs a mechanism to coordinate the motions and behaviors of robots so that they can perform effectively the tasks while interacting and cooperating with other robots. Therefore, this research concerns to designing a coordination mechanism to improve the efficiency and performance of multi-robot systems. In this thesis, the problems of coordination and motion design in multi-robot systems are discussed by using artificial potential field method. The mission of system is target tracking in a dynamic environment while avoiding any collision with other agents. Thus, we encounter three major problems to design the motion of robots: 1- target tracking, 2- collision avoidance and 3-the problem collision between robots. The problem of tracking a moving target has received a great deal of attention within the wide existing literature on mobile robots. The objective is to achieve tracking of a moving target by a group of mobile robots. To design the coordination and motion planning of robots, a total potential field composed of the target’s, robots’ and obstacles’ potential fields is formed so that it navigates the robots toward the target and provides a trajectory without any obstacle. Verification and simulation results validate the effectiveness of the designed multi-robot system. The target tracking problem is to estimate the state of a target1 based on inaccurate measurements from sensors. The estimation process contains many uncertainties; for example, the measurements are corrupted by noise, the origins of the measurements are unauthenticated, the motion of the target is unknown, etc. The target tracking problem has been studied in diverse research areas with many applications in mind. The motion tracking and estimation of moving objects in the vicinity of a mobile robot is also a fundamental capability for safe navigation. Populated environments are challenging to contemporary mobile robots. One of the main reasons is the presence of dynamic objects, whose motions are diverse (eg. due to pedestrians, bicycles, automobiles, etc). Since some objects move faster than the robot, motion detection and estimation for potential collision avoidance are the most fundamental skills that a robot needs to function effectively in dynamic environments. Needless to say, target tracking is a key enabler for robust motion estimation. The artificial potential field has some limitations. In this thesis, the problem of local minimum point is discussed and a novel approach for this problem is presented. The effectiveness of this approach is verified by simulation. Finally the thesis is concluded and some research problems are suggested. Keywords Coordination, Multi-robot system, Motion planning, Potential field method, Mobile robots