Path planning of mobile robot in an indoor environment using dynamic replanning and RRT stra alrorithm.

Abstract

Mobile robots are currently being introduced in many fields such as hospitality, healthcare, manufacturing, transportation, delivery. And research in the development of mobile robots is heading towards increasing their level of autonomy in performing different tasks of different levels of complexity. One of these tasks is path planning which is taking a significant amount of importance during the last decade, this is because mobile robots nowadays are requiring more intelligence in order to plan feasible paths in various types of environments. The sampling-based method RRT* is one of the most efficient algorithms to perform path planning because of their many advantages such as the adaptability with complex and large environments. This project introduces a path planning method for a ground wheeled mobile robot in an indoor environment in the presence of random obstacles using RRT* and Dynamic Replanning. the robot is uninformed about the obstacle’s positions, but informed about its static environment. and it combines both global and local path planning in order to achieve the goal. The results demonstrate successful execution of the algorithm using the same number of tree nodes.