Path Optimization Algorithms for Unmanned Aerial Vehicles (UAVS) Collision Avoidance

Unmanned aerial vehicles (UAVs) are frequently being applied at numerous applications and implementations in a tricky task. UAVs cannot operate effectively without path planning. Path planning is a key component of the overall performance of automation systems, particularly when it comes to industrial robots or drones. The mobility of an industrial drone is predetermined by a variety of algorithms that make up the industrial drone path planning system. The purpose of route planning algorithms is to identify safer, more efficient, collision-free, and least-cost travel paths for mobile robots and unmanned aerial vehicles. The path planning for Unmanned Aerial Vehicles (UAVs) can be categorized which is Conventional, Intelligent and Fusion algorithms. In this work, three algorithms were chosen which are A*, Hybrid A* and Dynamic Window Approach (DWA). All the algorithms were being tested in the multiple obstacle setup that had been created. Different obstacle setup was created to portray different complexity of the real situation in software simulation. All the data results for each algorithm were recorded and compared with each other. Based on the simulation generated, all path planning algorithms show the ability to reach the targeted point and avoid the obstacle in all maps created with different time computational and smoothness of the path. The results in terms of computational time and performance based on different complexity of the environment have shown a great potential for automatic UAVs path planning with collision avoidance in a known environment.