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A Multi-Sensor Environmental Perception System for an Automatic Electric Shovel Platform.

Xudong Li1,2, Chong Liu2,3,4, Jingmin Li2,3,4

  • 1School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, China.

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Summary
This summary is machine-generated.

This study introduces an intelligent electric shovel platform with an advanced environmental sensing system using RTK, IMU, and LiDAR. The system improves safety and efficiency in mining by reducing data processing and achieving high measurement accuracy.

Keywords:
electrical shovelenvironmental perception systemmultiple sensorspoint cloud processing

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Area of Science:

  • Robotics and Automation
  • Sensor Fusion
  • Environmental Perception

Background:

  • Electric shovels face challenges in performance due to complex environments and operator skill.
  • Improving safety and efficiency in mineral extraction requires autonomous operation technology.

Purpose of the Study:

  • To propose an experimental platform for intelligent electric shovel research.
  • To develop an intelligent environmental sensing/perception system for autonomous electric shovels.

Main Methods:

  • Integration of RTK, IMU, and LiDAR sensors for environmental perception.
  • Synchronization and fusion of data from two 2D-LiDARs to create a 3D point cloud.
  • Development of a novel point cloud processing algorithm for noise filtering and data compression.

Main Results:

  • The proposed system effectively reduces LiDAR point cloud data while preserving object characteristics.
  • Achieved an overall measurement error within 50 mm, meeting application requirements.
  • Demonstrated improved system efficiency and accuracy in outdoor environments.

Conclusions:

  • The developed intelligent environmental perception system significantly enhances electric shovel performance.
  • The experimental platform provides a valuable tool for advancing autonomous operation in heavy industry.
  • This research holds significant engineering value for improving electric shovel serviceability and operational safety.