Three-dimensional positioning algorithm for converter station patrol inspection based on multi-sensor filtering

Qiang Sun; Jiangsheng Yu; Zhenliang Chen; Xi Zhang; Qihao Zhong

doi:10.1117/12.3029135

6 May 2024 Three-dimensional positioning algorithm for converter station patrol inspection based on multi-sensor filtering

Qiang Sun, Jiangsheng Yu, Zhenliang Chen, Xi Zhang, Qihao Zhong

Author Affiliations +

Proceedings Volume 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024); 1310739 (2024) https://doi.org/10.1117/12.3029135
Event: Fourth International Conference on Sensors and Information Technology (ICSI 2024), 2024, Xiamen, China

Abstract

In order to improve the three-dimensional positioning accuracy of sensor to converter station inspection robots in unknown environments, a three-dimensional positioning algorithm for converter station inspection based on multi-sensor filtering was studied. Construct a motion information sensing model for the inspection robot in the converter station based on correcting multiple sensors, and use laser radar sensors and IMU sensors to respectively sense the three dimensional coordinate information, angular velocity, and acceleration information of the inspection robot in the converter station; Use the multi sensor correction method based on neural networks to correct the drift error of perceptual information; Through the inspection 3D positioning algorithm based on Kalman filter, the corrected perceptual positioning information is fused and filtered, and the 3D coordinates of the inspection robot in the converter station are estimated to complete the auxiliary work of the inspection 3D positioning in the converter station. In the experiment, the algorithm can locate the dynamic three-dimensional coordinates of the inspection robot in the converter station, and the mean square error of the positioning results is less than 0.05.

Citation Download Citation

Qiang Sun, Jiangsheng Yu, Zhenliang Chen, Xi Zhang, and Qihao Zhong "Three-dimensional positioning algorithm for converter station patrol inspection based on multi-sensor filtering", Proc. SPIE 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024), 1310739 (6 May 2024); https://doi.org/10.1117/12.3029135

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KEYWORDS

Inspection

Robots

Sensors

Neural networks

Tunable filters

Signal filtering

LIDAR

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