Image Acquisition Quality Optimization for Environmental Tests Based on an Intelligent Inspection Robot

HUANG Lun; ZHU Yuqin; SHU Chang; WU Xinrui; HE Yanru; ZHOU Junyan; HE Qiongyao; SUN Shaoxin; HE Dehong

doi:10.7643/issn.1672-9242.2026.04.017

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Equipment Environmental Engineering ›› 2026, Vol. 23 ›› Issue (4) : 178-184. DOI: 10.7643/issn.1672-9242.2026.04.017

Environmental Test and Observation

Image Acquisition Quality Optimization for Environmental Tests Based on an Intelligent Inspection Robot

HUANG Lun^1,2, ZHU Yuqin¹, SHU Chang¹, WU Xinrui¹, HE Yanru¹, ZHOU Junyan¹, HE Qiongyao¹, SUN Shaoxin², HE Dehong³

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Abstract

The work aims to address the issues of image defocusing, tilting, and other quality problems caused by pose shifts of intelligent inspection robots due to uneven ground in natural environmental test sites and enhance data acquisition efficiency. An integrated optimization method combining a robotic system with intelligent algorithms was proposed. Firstly, a dual localization mechanism integrating initial positioning based on the BeiDou satellite and semantic map with secondary positioning based on digital tag recognition was adopted to correct the robot's walking trajectory deviation. Subsequently, an innovative border-expanding objectness detection algorithm was used to accurately segment the overall image of the test rack and locate each sample. Finally, combined with the principle of binocular vision, the optimal shooting parameters (distance, angle, focal length) were dynamically calculated to ensure that the target was vertically centered and clearly imaged. Experimental results indicated that after optimization by this method, the image quality captured by the robot significantly improved. The Natural Image Quality Evaluator (NIQE) score was optimized from 4.91 to 4.03, and the image qualification rate increased from 75% to 95%, which was comparable to manual acquisition. Meanwhile, the data acquisition frequency increased from once every three months manually to once per day, representing an approximately 90-fold efficiency improvement. This work establishes an automated, high-precision image acquisition scheme that effectively overcomes the limitations of manual acquisition and traditional robot inspection, which significantly enhances the timeliness, standardization, and scientific value of data acquisition in natural environmental tests, providing reliable technical support for research on equipment environmental effects.

Key words

intelligent inspection robot / environmental test / data acquisition / image quality optimization / machine vision

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HUANG Lun, ZHU Yuqin, SHU Chang, WU Xinrui, HE Yanru, ZHOU Junyan, HE Qiongyao, SUN Shaoxin, HE Dehong. Image Acquisition Quality Optimization for Environmental Tests Based on an Intelligent Inspection Robot[J]. Equipment Environmental Engineering. 2026, 23(4): 178-184 https://doi.org/10.7643/issn.1672-9242.2026.04.017

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Funding

National Natural Science Foundation of China (U22A20101); Key Project of Chongqing Technology Innovation and Application Development Special Program (CSTB2022TIAD-CUX0015)