A Review on UAV Path Planning Optimization based on Motion Planning Algorithms: Collision Avoidance and Challenges

This research study is focused on surveying Unmanned Aerial Vehicles (UAVs) Path planning to reach the destination in an efficient manner. The path planning has been challenging task working towards various fields. This review provides a comprehensive survey on obstacle avoidance methods for UAVs. It is an extensive survey on various obstacle avoidance approaches like a motion planning algorithms, Genetic algorithm for Ground node communication and Ant colony algorithm for best optimal paths. These algorithms have a high convergence speed and stability. This study investigates united UAV to UAV (U2U) communication in an uplink as well as downlink wireless cellular network. Here U2U nodes act as relays in an uplink and coexists in downlink cellular networks. The development of U2U is driven by UAV operators to harvest short range communication for improving network performance. The large number of nodes are connected in a wireless communication network; it is a very difficult to find the best route plan because routing is a complex task in rescue operation. The review of intelligent path planning approach is used to solve complex route planning tasks in a wireless communication networks. Obstacle detection, avoid clashes, system controlling and path planning or trajectories are the key parts of the UAVs to navigate autonomously.