UAV path planning based on improved TD3 algorithm
Chao Lv, Baoquan Xu, C. Shi · 2023
For the UAV path planning problem in complex unknown environments, a dual delayed deep deterministic policy gradient algorithm based on composite experience replay is proposed. First, the TD3 algorithm and LSTM neural network are combined, and then the experience replay mechanism and reward function are improved to allow better obstacle avoidance in both dynamic and static environments. By building an environment for simulation experiments, the results show that the algorithm is more efficient and stable in obstacle avoidance compared with the original algorithm, and can help UAVs perform better path planning in unknown environments where multiple obstacles exist.