Unmanned aerial vehicle non-stop inspection and obstacle avoidance route planning based on reinforcement learning cuckoo search algorithm

Key Points

• The aim is to develop a route planning algorithm for unmanned aerial vehicles (UAVs) that can effectively avoid obstacles.
• Developed a route planning algorithm based on reinforcement learning and cuckoo search.
• Conducted simulations to test the algorithm's efficiency in obstacle avoidance.
• Analyzed the performance of the UAV's navigation in various environments.
• The proposed algorithm successfully avoided obstacles during navigation.
• It showed an improvement in inspection efficiency compared to traditional methods.
• The simulations indicated a significant reduction in travel time for inspections.

Abstract