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Real-Time Motion Tracking for Indoor Moving Sphere Objects with a LiDAR Sensor.

Lvwen Huang1,2, Siyuan Chen3, Jianfeng Zhang4

  • 1College of Information Engineering, Northwest A&F University, Xianyang 712100, China. huanglvwen@nwafu.edu.cn.

Sensors (Basel, Switzerland)
|August 24, 2017
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Summary
This summary is machine-generated.

This study presents real-time 3D object tracking using LiDAR data and advanced filters. The Kalman filter offers efficiency, while the adaptive particle filter provides robustness and precision for moving spherical targets.

Keywords:
3D LiDARKalman filteradaptive particle filterobject tracking

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Area of Science:

  • Computer Vision
  • Robotics
  • Sensor Fusion

Background:

  • Object tracking is vital for autonomous systems like robots and navigation aids.
  • Real-time processing of 3D point cloud data from sensors like LiDAR is challenging.

Purpose of the Study:

  • To achieve real-time visualization and tracking of moving spherical targets using 3D LiDAR data.
  • To compare the performance of Kalman and adaptive particle filters for object tracking in complex environments.

Main Methods:

  • Utilized Velodyne Lidar (VLP-16) for 3D point cloud acquisition.
  • Implemented preprocessing, ground segmentation, Euclidean clustering, and View Feature Histogram (VFH) feature extraction.
  • Applied Kalman filter and adaptive particle filter for real-time position estimation of a moving spherical target.

Main Results:

  • Both Kalman and adaptive particle filters were validated in diverse scenarios, including partial occlusion and varying speeds/trajectories.
  • Kalman filter demonstrated high efficiency.
  • Adaptive particle filter exhibited high robustness and precision.

Conclusions:

  • The developed system enables effective real-time 3D object tracking using LiDAR.
  • The choice between Kalman and adaptive particle filters depends on specific application requirements for efficiency versus robustness/precision.
  • Potential applications include fruit identification, robot navigation, and control systems.