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Distributed Multi-Antenna Positioning for Automatic-Guided Vehicle.

Xinyuan An1,2, Sihao Zhao1, Xiaowei Cui1

  • 1Department of Electronic Engineering, Tsinghua University, Beijing 100084, China.

Sensors (Basel, Switzerland)
|February 26, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a multi-antenna positioning system for automatic-guided vehicles (AGVs) to overcome signal blockage issues. The system enhances localization accuracy and availability in challenging environments.

Keywords:
Levenberg–Marquardtautomatic-guided vehiclesdistributed multi-antenna positioning

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Area of Science:

  • Robotics
  • Navigation Systems
  • Signal Processing

Background:

  • Radio-based positioning is crucial for automatic-guided vehicles (AGVs) but is hindered by obstacles and cargo blocking radio signals, degrading localization performance.
  • Existing systems often suffer from reduced accuracy and availability in harsh industrial environments.

Purpose of the Study:

  • To propose a novel distributed multi-antenna positioning system for AGVs to enhance localization accuracy and availability.
  • To address the limitations of single-antenna systems in environments with signal propagation challenges.

Main Methods:

  • A distributed multi-antenna system with synchronous antennas placed on AGV corners was developed.
  • The Levenberg-Marquardt algorithm was employed to solve nonlinear pseudo-range equations.
  • A coarse estimator using antenna displacement knowledge was introduced for global optimal solutions.

Main Results:

  • The proposed multi-antenna system demonstrated improved availability compared to single-antenna systems.
  • Decimeter-level positioning accuracy was achieved under Gaussian noise (0.2 m standard deviation).
  • The algorithm approached the theoretical Cramer-Rao lower bound for positioning accuracy.

Conclusions:

  • The distributed multi-antenna system significantly improves AGV positioning availability and accuracy, especially in obstructed environments.
  • The coarse estimation step enhances global optimal solutions, and yaw angle information can further refine accuracy.
  • This approach offers a robust solution for high-precision AGV navigation in industrial settings.