TY - GEN
T1 - A Deep Q-Network-Based Algorithm for Obstacle Avoidance and Target Tracking for Drones
AU - Guo, Jingrui
AU - Huang, Chao
AU - Huang, Hailong
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/10
Y1 - 2023/10
N2 - This paper introduces a novel algorithm, refer to NEWDQN, which is based on the deep Q-network (DQN) framework. The primary objective of this algorithm is to optimize the successful rate both in autonomous drone obstacle avoidance and target tracking tasks, while this algorithm can also improve the drawbacks of the previous algorithm in convergence. Furthermore, the algorithm endows the drone with environment perception capabilities and incorporates a direction-based reward-penalty function into the reward function, enhancing the drone's generalization ability and overall performance. Extensive simulations demonstrate that compared to conventional DQN and Double DQN (DDQN) algorithms, NEWDQN exhibits faster convergence speed, shorter tracking paths, and more robust adaptability to different environments.
AB - This paper introduces a novel algorithm, refer to NEWDQN, which is based on the deep Q-network (DQN) framework. The primary objective of this algorithm is to optimize the successful rate both in autonomous drone obstacle avoidance and target tracking tasks, while this algorithm can also improve the drawbacks of the previous algorithm in convergence. Furthermore, the algorithm endows the drone with environment perception capabilities and incorporates a direction-based reward-penalty function into the reward function, enhancing the drone's generalization ability and overall performance. Extensive simulations demonstrate that compared to conventional DQN and Double DQN (DDQN) algorithms, NEWDQN exhibits faster convergence speed, shorter tracking paths, and more robust adaptability to different environments.
UR - http://www.scopus.com/inward/record.url?scp=85187289673&partnerID=8YFLogxK
U2 - 10.1109/SMC53992.2023.10393953
DO - 10.1109/SMC53992.2023.10393953
M3 - Conference article published in proceeding or book
AN - SCOPUS:85187289673
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 4530
EP - 4535
BT - 2023 IEEE International Conference on Systems, Man, and Cybernetics
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023
Y2 - 1 October 2023 through 4 October 2023
ER -