This paper presents the PSO-CF²-mt motion planning approach that we propose for two wheeled mobile robots for tracking moving targets in known dynamic environments. The Particle Swarm Optimization Canonical Force Field (PSO-CF²) is a mobile robot motion planning approach that we have previously proposed for static and dynamic environments[9]. PSO-CF²-mt is an improved version of PSO-CF² to become capable of tracking a moving target. The basic concept of PSO-CF²-mt is to generate a continually changing parameterized Force Field for the robot based on the characteristics of all objects presents in the environment. The simulation results prove clearly the ability of PSO-CF2-mt to follow and reach a moving target by choosing the shortest and the most secure paths whatever the complexity of the environment and the form of the target's trajectory. A comparative study with APF (Artificial Potential Field) proves the quality of our proposed approach.