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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...

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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

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An Extensible Positioning System for Locating Mobile Robots in Unfamiliar Environments.

Xiaosu Xu^1,2, Xinghua Liu^3,4, Beichen Zhao^5,6

¹Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Southeast University, Nanjing 210096, China. xxs@seu.edu.cn.

Sensors (Basel, Switzerland)

|September 22, 2019

Summary

This study introduces an extensible mobile robot positioning system using ultra-wideband (UWB) and inertial measurement units (IMU). The system achieves precise localization in unknown environments, even when extended with new anchors.

Keywords:

data fusion extensible positioning system indoor positioning maximum correntropy Kalman filter mobile robot unfamiliar environment

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Area of Science:

Robotics
Navigation Systems
Sensor Fusion

Background:

Accurate mobile robot localization is crucial for autonomous operation, especially in unknown or dynamic environments.
Existing systems often require complex infrastructure, including inter-anchor communication and clock synchronization.

Purpose of the Study:

To propose an extensible positioning system for mobile robots that does not require inter-anchor communication or clock synchronization.
To enable robust localization in unfamiliar environments by allowing system extension with new anchors.

Main Methods:

A system combining stereo cameras, an inertial measurement unit (IMU), and an ultra-wideband (UWB) network.
Recursive least squares (RLS) for estimating new anchor positions.
Maximum correntropy Kalman filter (MCKF) for fusing UWB and IMU data.
Visual SLAM and UWB system comparison for initial attitude calculation.

Main Results:

Achieved a root mean square error (RMSE) of 0.130 m with all anchors.
Demonstrated robust performance in unfamiliar environments with an RMSE of 0.131 m.
New anchor position estimation achieved an Euler distance RMSE of 0.061 m.

Conclusions:

The proposed extensible positioning system offers high accuracy and adaptability for mobile robots.
The system effectively localizes robots in unknown environments by seamlessly integrating new UWB anchors.
The method overcomes limitations of traditional UWB systems by removing communication and synchronization requirements.