Collision avoidance and path planning for mobile robots based on state estimation approach

Planning a collision-free path while preserving processing time and minimizing cost function has been considered a significant challenge in developing an Autonomous Mobile Robot (AMR). Various optimization techniques for avoiding obstacles and path planning problems have been proposed recently. But, the computation time for executing these techniques is comparatively higher and has lesser accuracy. In this paper, the State Estimation Obstacle Avoidance (SEOA) algorithm has been proposed for estimating the position and velocity of both of the wheels of the AMR. Moreover, this algorithm has been also applied in path planning for reaching the destination point in minimum computational time. Five different positions of static obstacle are demonstrated in a real time static environment where the proposed SEOA algorithm has been compared with state-of-the-art path planning algorithms such as A* and VFH. The simulation results demonstrate that the proposed algorithm takes lesser computational time to generate the collision free path when compared to other mentioned algorithms.