Abstract: Robot path planning is an imperative fragment in enlargement of the autonomous systems. Abundant stratagems have been proposed in literature concerning mobile robots but the trajectory planning for manipulators is substantially more challenging meanwhile all-inclusive structure can move & produce accidents with the adjoining obstacles. APF (Artificial Potential Field) technique is extensively used for the mobile robots path planning due to its sophisticated mathematical analysis & minimalism. Nonetheless, this method has some characteristic shortcomings in the path planning. This paper benevolences newfangled effectual method for the autonomous mobile robot path planning in the comprehensive known surroundings. We are primarily considering an artificial potential field process with the amended layers of design after that gain coefficient of repulsion are optimized through proposed the genetic algorithm by considering repulsion coefficient as our objective function, as we know that force of repulsion plays an important role in the path planning. A more efficient technique used here is backtracking model. In this manner, we have to save trace of running algorithm to select the shortest path. A novel total potential concept is also proposed which consider effect of obstacles near target & conception of the velocity based force calculation is also derived in the case of movable obstacles or target. Simulation results show that this technique has a better, accurate & optimized results than other common approaches such as bug & artificial potential field.
Keywords: Articial potential field, Robot path planning, Mobile Robot, Genetic Algorithm, Search Optimization, Backtracking, Potential Learning.