Research on the Positioning and Recognition of an Intelligent Inspection Robot in Substations
Chongqing Three Gorges Vocational College
No. 8 Kelong Road, Wanzhou, Chongqing 404155, China
The substation inspection robot follows the set path when working autonomously, and accurate positioning of the robot while moving is required to ensure that the route does not deviate. This study briefly introduces a substation inspection robot, an odometer-based positioning algorithm, radio frequency identification (RFID), and a machine vision-based positioning algorithm, and improves the former algorithm by RFID. Subsequently, the three positioning algorithms were compared. The results showed that the RFID+machine vision-based positioning algorithm exhibited the highest accuracy among the three algorithms tested under the same cycle number, and its positioning error remained stable as the cycle number increased.
-  J. L. Cao, Y. Luo, and Z. Li, “Study on 3-D Laser-Scanning-Based Machine Vision System for Robotic Construction Vehicles,” Adv. Mater. Res., Vols.591-593, pp. 1391-1395, 2012.
-  Y. Campos, H. Sossa, and G. Pajares, “Spatio-temporal analysis for obstacle detection in agricultural videos,” Appl. Soft Comput., Vol.45, pp. 86-97, 2016.
-  H. Kurita, M. Iida, W. Cho, and M. Suguri, “Rice Autonomous Harvesting: Operation Framework,” J. Field Robot., Vol.34, No.6, pp. 1084-1099, 2017.
-  L. Dong and J. Lv, “Research on Indoor Patrol Robot Location based on BP Neural Network,” IOP Conf. Ser. Earth Environ. Sci., Vol.546, No.5, 052035, 2020.
-  X. Zhang and X. Guo, “UWB/IMU integrated inspection robot positioning in underground substation,” J. Phys. Conf. Ser., Vol.1976, No.1, 012022, 2021.
-  O. Sokolov, A. Mreła, M. Józefowicz, K. Rydel, and S. Meszyński, “Positioning a mobile robot in a closed area with a map of markers,” J. Educ. Health Sport, Vol.9, No.4, pp. 573-579, 2019.
-  A. Motroni, A. Buffi, P. Nepa, and B. Tellini, “Sensor-Fusion and Tracking Method for Indoor Vehicles with Low-Density UHF-RFID Tags,” IEEE T. Instrum. Meas., Vol.70, 8001314, 2020.
-  Y. J. Mon, “Machine vision based sliding fuzzy-PDC control for obstacle avoidance and object recognition of service robot platform,” J. Intell. Fuzzy Syst., Vol.28, No.3, pp. 1119-1126, 2015.
-  Z. Liu, Y. He, C. Wang, and R. Song, “Analysis of the Influence of Foggy Weather Environment on the Detection Effect of Machine Vision Obstacles,” Sensors, Vol.20, No.2, 349, 2020.
-  V. V. Meshram, K. Patil, V. A. Meshram, and F. C. Shu, “An Astute Assistive Device for Mobility and Object Recognition for Visually Impaired People,” IEEE T. Hum. Mach. Syst., Vol.49, No.5, pp. 449-460, 2019.
-  R. Kumar, S. Sarangi, A. Shukla, and M. G. Arakere, “Location guidance of robots using local positioning system,” IOP Conf. Ser. Mater. Sci. Eng., Vol.402, 012040, 2018.
-  J. Zhang, J. Huang, and W. Chen, “Centralized management system of intelligent inspection robot based on wireless sensor,” Microprocess. Microsy., Vol.2020, No.46, 103409, 2020.
-  C. Tu, S. Jin, K. Zheng, X. Wang, and S. Sun, “Support and Positioning Mechanism of a Detection Robot inside a Spherical Tank,” Chin. J. Mech. Eng., Vol.34, No.1, 5, 2021.
-  M. Endo, T. Kakizaki, Y. Nakamura, T. Hebiishi, and K. Otani, “Design of a Tendon-Drive Manipulator for Positioning a Probe of a Cooperative Robot System for Fault Diagnosis of Solar Panels at Mega Solar Power Plant,” ROMANSY 21 – Robot Design, Dynamics and Control, Vol.569, pp. 321-328, 2016.
-  M. Śmieja, “ZigBee phase shift measurement approach to mobile inspection robot indoor positioning techniques,” Diagnostyka, Vol.19, No.3, pp. 101-107, 2018.
-  M. Seeger, “Accurate Positioning for Robot Painting,” IST Int. Surf. Technol., Vol.8, No.2, pp. 58-59, 2015.
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