Zhuoyan Xie1, Qi Wang1,*, Bin Kong2,*, Shang Gao1
CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3013-3027, 2025, DOI:10.32604/cmc.2025.064147
- 03 July 2025
Abstract In the current era of intelligent technologies, comprehensive and precise regional coverage path planning is critical for tasks such as environmental monitoring, emergency rescue, and agricultural plant protection. Owing to their exceptional flexibility and rapid deployment capabilities, unmanned aerial vehicles (UAVs) have emerged as the ideal platforms for accomplishing these tasks. This study proposes a swarm A*-guided Deep Q-Network (SADQN) algorithm to address the coverage path planning (CPP) problem for UAV swarms in complex environments. Firstly, to overcome the dependency of traditional modeling methods on regular terrain environments, this study proposes an improved cellular decomposition… More >
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