PATH PLANNING FOR DRONES

Path Planning for autonomous robots is finding the shortest optimum path from a given source to a destination while also taking obstacles into consideration. In our case the autonomous robots are drones.. The algorithm needs to work dynamically and continuously as the drone is traversing as all the information about the environment would not be given initially but will be perceived as traversing. Thus the purpose of this project is to study and compare 3 methods for path planning on drones with low-end hardware, thus the algorithm needs to have time and space complexity less than or equal to what is required. The algorithms that are studied are path planning using fuzzy logic, path planning using reinforcement learning, and modified A-star algorithm.