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Acta Armamentarii ›› 2025, Vol. 46 ›› Issue (6): 240583-.doi: 10.12382/bgxb.2024.0583

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Construction of Special Obstacle Dataset and Detection Algorithm Evaluation System in Air-ground Collaborative Scenarios

LENG Chengyu, ZHAO Jin*(), LIU Chang, YANG Shifeng   

  1. School of Mechanical Engineering, Guizhou University, Guiyang 550025, Guizhou, China
  • Received:2024-07-15 Online:2025-06-28
  • Contact: ZHAO Jin

Abstract:

The recognition and handling of special obstacles are critical to ensuring the safe operation of ground equipment in air-ground collaborative scenarios.To address the lack of data samples in unstructured environments,a detection dataset comprising 33124 images is developed,featuring a wide range of typical special obstacles to support the recognition tasks in complex scenes.A comprehensive evaluation index integrating the category information and localization accuracy is designed to enhance the objectivity and reliability of algorithm performance comparisons.Additionally,a passability analysis method is proposed,which combines the physical properties with the environmental semantics to guide path planning for unmanned ground systems.Experimental results demonstrate that the proposed dataset and evaluation framework significantly improve detection accuracy,and the method effectively identifies typical obstacles such as potholes and water surfaces in unstructured environments.

Key words: special obstacle detection, ground-air collaboration, dataset construction, passability strategy

CLC Number: