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Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR

Conventional mobile robots employ LIDAR for indoor global positioning and navigation, thus having strict requirements for the ground environment. Under the complicated ground conditions in the greenhouse, the accumulative error of odometer (ODOM) that arises from wheel slip is easy to occur during t...

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Autores principales: Long, Zhenhuan, Xiang, Yang, Lei, Xiangming, Li, Yajun, Hu, Zhengfang, Dai, Xiufeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269595/
https://www.ncbi.nlm.nih.gov/pubmed/35808314
http://dx.doi.org/10.3390/s22134819
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author Long, Zhenhuan
Xiang, Yang
Lei, Xiangming
Li, Yajun
Hu, Zhengfang
Dai, Xiufeng
author_facet Long, Zhenhuan
Xiang, Yang
Lei, Xiangming
Li, Yajun
Hu, Zhengfang
Dai, Xiufeng
author_sort Long, Zhenhuan
collection PubMed
description Conventional mobile robots employ LIDAR for indoor global positioning and navigation, thus having strict requirements for the ground environment. Under the complicated ground conditions in the greenhouse, the accumulative error of odometer (ODOM) that arises from wheel slip is easy to occur during the long-time operation of the robot, which decreases the accuracy of robot positioning and mapping. To solve the above problem, an integrated positioning system based on UWB (ultra-wideband)/IMU (inertial measurement unit)/ODOM/LIDAR is proposed. First, UWB/IMU/ODOM is integrated by the Extended Kalman Filter (EKF) algorithm to obtain the estimated positioning information. Second, LIDAR is integrated with the established two-dimensional (2D) map by the Adaptive Monte Carlo Localization (AMCL) algorithm to achieve the global positioning of the robot. As indicated by the experiments, the integrated positioning system based on UWB/IMU/ODOM/LIDAR effectively reduced the positioning accumulative error of the robot in the greenhouse environment. At the three moving speeds, including 0.3 m/s, 0.5 m/s, and 0.7 m/s, the maximum lateral error is lower than 0.1 m, and the maximum lateral root mean square error (RMSE) reaches 0.04 m. For global positioning, the RMSEs of the x-axis direction, the y-axis direction, and the overall positioning are estimated as 0.092, 0.069, and 0.079 m, respectively, and the average positioning time of the system is obtained as 72.1 ms. This was sufficient for robot operation in greenhouse situations that need precise positioning and navigation.
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spelling pubmed-92695952022-07-09 Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR Long, Zhenhuan Xiang, Yang Lei, Xiangming Li, Yajun Hu, Zhengfang Dai, Xiufeng Sensors (Basel) Article Conventional mobile robots employ LIDAR for indoor global positioning and navigation, thus having strict requirements for the ground environment. Under the complicated ground conditions in the greenhouse, the accumulative error of odometer (ODOM) that arises from wheel slip is easy to occur during the long-time operation of the robot, which decreases the accuracy of robot positioning and mapping. To solve the above problem, an integrated positioning system based on UWB (ultra-wideband)/IMU (inertial measurement unit)/ODOM/LIDAR is proposed. First, UWB/IMU/ODOM is integrated by the Extended Kalman Filter (EKF) algorithm to obtain the estimated positioning information. Second, LIDAR is integrated with the established two-dimensional (2D) map by the Adaptive Monte Carlo Localization (AMCL) algorithm to achieve the global positioning of the robot. As indicated by the experiments, the integrated positioning system based on UWB/IMU/ODOM/LIDAR effectively reduced the positioning accumulative error of the robot in the greenhouse environment. At the three moving speeds, including 0.3 m/s, 0.5 m/s, and 0.7 m/s, the maximum lateral error is lower than 0.1 m, and the maximum lateral root mean square error (RMSE) reaches 0.04 m. For global positioning, the RMSEs of the x-axis direction, the y-axis direction, and the overall positioning are estimated as 0.092, 0.069, and 0.079 m, respectively, and the average positioning time of the system is obtained as 72.1 ms. This was sufficient for robot operation in greenhouse situations that need precise positioning and navigation. MDPI 2022-06-25 /pmc/articles/PMC9269595/ /pubmed/35808314 http://dx.doi.org/10.3390/s22134819 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Long, Zhenhuan
Xiang, Yang
Lei, Xiangming
Li, Yajun
Hu, Zhengfang
Dai, Xiufeng
Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
title Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
title_full Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
title_fullStr Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
title_full_unstemmed Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
title_short Integrated Indoor Positioning System of Greenhouse Robot Based on UWB/IMU/ODOM/LIDAR
title_sort integrated indoor positioning system of greenhouse robot based on uwb/imu/odom/lidar
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269595/
https://www.ncbi.nlm.nih.gov/pubmed/35808314
http://dx.doi.org/10.3390/s22134819
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