In this paper, a novel path-following and obstacle avoidance control method is given for nonholonomic wheeled mobile robots (NWMRs), based on deep reinforcement learning. The model for path-following is investigated first, and then applied to the proposed reinforcement learning control strategy. The proposed control method can achieve path-following control through interacting with the environment of the set path. The path-following control method is mainly based on the design of the state and reward function in the training of the reinforcement learning. For extra obstacle avoidance problems in following, the state and reward function is redesigned by utilizing both distance and directional perspective aspects, and a minimum representative value is proposed to deal with the occurrence of multiple obstacles in the path-following environment. Through the reinforcement learning algorithm deep deterministic policy gradient (DDPG), the NWMR can gradually achieve the path it is required to follow and avoid the obstacles in simulation experiments, and the effectiveness of the proposed algorithm is verified.
A foreign object on an airport runway is also called a foreign object, that is, some foreign material, debris or object that may cause damage to the aircraft, such as scattered aircraft parts, luggage parts, wildlife, etc. On airport runway, there are mainly the activities of aircraft, less activities of human. As a result, most of the foreign objects on runway are parts that fall off the aircraft, mostly made of metal. Due to the strong suction of aircraft engines and high speed crushing of tires during take-off and landing, aircraft is relatively fragile compared with foreign bodies, and the presence of foreign bodies on the runway can cause serious damage to the structure of aircraft. A tiny object sucked into the engine could cause damage to the blades, and debris could accumulate in the machinery, affecting the plane’s normal operation. In view of the above problems, the research and realization of the FOD detector of airport runway are carried out in depth.
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