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April 4, 2026International Journal of Systems Control and Communications0 citations

Hierarchical reinforcement learning-based UAV path planning and energy management

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HLHaitao LiCCChao CheYLYuexin Liu

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

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69d0af83659487ece0fa573ehttps://doi.org/10.1504/ijscc.2026.10077405
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