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October 29, 2025Science DiscoveryOpen Access

Key Technologies for Target-Driven Autonomous UAV Inspection in Power Grids Based on Reinforcement Learning

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Authors

SGShun-Feng GaoQLQinghua LiuMSMin Sun

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Overview

Field experiments demonstrate improved efficiency and safety in power grid UAV inspections, highlighting reinforcement learning applications.

Key Points

  • Operational safety increased due to a flight control method incorporating reinforcement learning, improving UAV inspections.
  • Field experiments indicated 30% greater flight path planning efficiency when using a holistic technical framework for power grid evaluations.
  • Developed risk assessment techniques enhanced obstacle recognition accuracy alongside dynamic path planning in UAV operations.
  • Digital transformation of power grids is facilitated through intelligent UAV designs optimizing efficiency and overall inspection intelligence.

Cite This Study

Gao et al. (2025) studied this question.

synapsesocial.com/papers/69254f92c0ce034ddc359b25https://doi.org/10.11648/j.sd.20251305.13
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Also Consider

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  1. 1A Conceptual Framework for UAV Integration into National Power Grid Inspection Programs2018 · 18 citations
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  4. 4A Review of UAV Applications in Electrical Transmission Line Inspection: Methods, Technologies, and Challenges2019 · 18 citations
  5. 5Deep Learning-Based Visual Analytics for Efficiency and Safety Optimization in Power Infrastructure2026 · 6 citations