Hierarchical reinforcement learning-based UAV path planning and energy management

Key Points

• To explore the application of hierarchical reinforcement learning for optimizing path planning and energy management in UAV operations.
• Developed a hierarchical reinforcement learning framework for UAV path planning.
• Implemented energy management strategies into the path planning algorithm.
• Conducted simulations to evaluate the effectiveness of proposed models.
• Achieved significant improvements in energy efficiency during UAV flights.
• Demonstrated successful navigation through complex environments using the proposed strategies.
• Showed increased operational range and reduced mission costs.

Abstract