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The rapid development of China’s automotive industry has driven advancements in inspection vehicle technology, with an increasing number of intelligent inspection vehicles being applied in urban management and infrastructure monitoring. They not only enhance inspection efficiency but also collect data in real time, aiding decision-makers in making more informed judgments. As electrification and autonomous driving technologies advance, the functions and application scenarios of inspection vehicles will further expand, becoming the “eyes” and “hands” of urban management. However, due to complex backgrounds, lighting conditions, and limitations of individual sensors, the detection accuracy of single-sensor-based inspection technologies still needs improvement. To address this, this paper proposes constructing a multi-sensor system for unmanned inspection vehicles, conducting systematic research on issues such as target detection, data processing, and information fusion for intelligent inspection perception systems, and designing a complete experimental plan to validate the constructed perception system. Experimental results indicate that this approach effectively resolves the issue.

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Research on the Key Technology of Multi-sensor Fusion Environment Perception Based on Unmanned Patrol Vehicle

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Min Lin,
  • Dongsheng Lin,
  • Pengxin Yue,
  • Wenyang Chi,
  • Xinrui Ma,
  • Yingbing Huang

摘要

The rapid development of China’s automotive industry has driven advancements in inspection vehicle technology, with an increasing number of intelligent inspection vehicles being applied in urban management and infrastructure monitoring. They not only enhance inspection efficiency but also collect data in real time, aiding decision-makers in making more informed judgments. As electrification and autonomous driving technologies advance, the functions and application scenarios of inspection vehicles will further expand, becoming the “eyes” and “hands” of urban management. However, due to complex backgrounds, lighting conditions, and limitations of individual sensors, the detection accuracy of single-sensor-based inspection technologies still needs improvement. To address this, this paper proposes constructing a multi-sensor system for unmanned inspection vehicles, conducting systematic research on issues such as target detection, data processing, and information fusion for intelligent inspection perception systems, and designing a complete experimental plan to validate the constructed perception system. Experimental results indicate that this approach effectively resolves the issue.