Optimization of the CF2 mobile robot motion planning approach and adaptation for moving targets
Safa Ziadi, Mohamed Njah · 2022 8th International Conference on Control, Decision and Information Technologies (CoDIT) · 2022
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-CF2to 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.