Path planning for a mobile robot in a dynamic environment

Nowadays, mobile robots work under the dynamic environments like manufacturing industries with machinery parts as moving objects and are using many techniques for navigation, obstacle avoidance, and localization. In this work we are using pioneer 2 DX mobile robot for experiments. This paper focuses on development of algorithms with the integration of path planning by potential field method and Monte Carlo localization method for navigation, obstacle avoidance, and localization of the mobile robot in a dynamic environment like in manufacturing industry. The path planning algorithms has divided into two submodules, one is global path planning which uses visibility graph with A* search method and another is local path planning which uses potential field method to avoid the obstacles. The image processing is used to get the working environment information from the global camera. The robot control program uses MCL algorithms with gradient path planning for continuous localization. User-friendly path planning software PMADE V 2.0 is developed. PMADE v 2.0 is used for image processing, path planning, simulation of robot navigation, real robot manual control and real robot automatic control for navigation in dynamic environment from position data of the simulator.