Improvement Of Potential Field Algorithm for Robot Path Planning (original) (raw)

In this project, we improved and implemented the Artificial Potential Field Algorithms (APF) for path planning, then the robot uses the path planning to navigate from the starting position to the goal position with avoiding the obstacles collision. The path planning generated by the APF is an optimal path, shortest distance to the goal. We have investigated three scenarios to create the path planning. Forst scenario, generating path planning with one obstacle. The second scenario, generating path planning with two obstacles. The third scenario, generating the path planning with two obstacles but with different parameters of the spread of attraction, the spread of repulsive, the strength of attraction, and the strength of repulsive , then, the optimal path planning among those parameters founded in scenario 3. We tested two local minima and simulated with APF algorithm then we compare the results for the better path planning. An improvement APF has been tested and simulated for the local minima problem