Real-time obstacle avoidance with deep reinforcement learning Three-Dimensional Autonomous Obstacle Avoidance for UAV

At present, drones are rapidly developing in the aviation industry and are applied to all aspects of life. However, letting drones autonomously avoid obstacles is still the focus of research by aviation scholars at this stage. However, the current automation is mostly based on human experience to determine the obstacle avoidance strategy of UAV. And the method only rely on the machine to avoid obstacle is very few. In this paper, the UAV collect visual and distance sensor information to make autonomous obstacle avoidance decision through the deep reinforcement learning algorithm, and the algorithm is tested in the v-rep simulation environment.