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<p>The outdoor industrial environments are inherently complex, which pose significant challenges to unmanned aerial vehicles (UAVs) trajectory generation. We have enhanced the EGO-planner algorithm for the application of UAVs on power line inspection in three key areas. First, we introduce a risk assessment mechanism that identifies hazardous areas, marking them as unfeasible regions in the map for refinement. Next, environmental factors are integrated into the local planner’s assessment, optimizing the selection of local target points. Finally, the initial state of replanning is tightly coupled with the real-time state of the UAVs, ensuring the elimination of cumulative execution errors. Our results demonstrate that the proposed algorithm significantly improves UAV adaptability in complex environments, outperforming traditional methods. Deployed on DJI’s Matrice 300 RTK UAV, the experimental findings show that our approach effectively supports trajectory generation for outdoor power line inspection in challenging outdoor environments.</p>

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An improved trajectory generation algorithm for outdoor power line inspection

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Bin Lan,
  • Minfeng Xing,
  • Haitao Lv

摘要

The outdoor industrial environments are inherently complex, which pose significant challenges to unmanned aerial vehicles (UAVs) trajectory generation. We have enhanced the EGO-planner algorithm for the application of UAVs on power line inspection in three key areas. First, we introduce a risk assessment mechanism that identifies hazardous areas, marking them as unfeasible regions in the map for refinement. Next, environmental factors are integrated into the local planner’s assessment, optimizing the selection of local target points. Finally, the initial state of replanning is tightly coupled with the real-time state of the UAVs, ensuring the elimination of cumulative execution errors. Our results demonstrate that the proposed algorithm significantly improves UAV adaptability in complex environments, outperforming traditional methods. Deployed on DJI’s Matrice 300 RTK UAV, the experimental findings show that our approach effectively supports trajectory generation for outdoor power line inspection in challenging outdoor environments.