Papers
21
Total Citations
435
H-Index
11
About
Jacek Wodecki is a prominent researcher specializing in robotics, autonomous inspection systems, and predictive maintenance for the mining industry, with a particular focus on underground and opencast environments. His work sits at the intersection of machine vision, infrared thermography, and intelligent diagnostic systems, addressing one of mining's most pressing challenges: the safe and efficient monitoring of belt conveyor infrastructure. Wodecki's most influential contributions center on developing unmanned ground vehicle (UGV) platforms capable of autonomously detecting faults in belt conveyor idlers — components numbering in the thousands across mining operations. His 2020 paper on infrared thermography for overheated idler detection has garnered 87 citations, while related work on RGB-infrared image fusion and acoustic signal-based diagnostics have collectively attracted over 100 additional citations, reflecting the field's strong uptake of his methodologies. Beyond conveyors, Wodecki has advanced robotic systems for rescue support in hazardous underground conditions, contributed to SLAM-based 3D mapping for autonomous vehicles, and explored cloud-based predictive maintenance frameworks. His CNN-based approaches to automated fault classification further demonstrate his embrace of deep learning for industrial diagnostics. Collectively, his research has meaningfully shaped how the mining industry approaches safety, automation, and condition monitoring in its most demanding environments.
Research Focus
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Top Papers
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- 6Why Should Inspection Robots be used in Deep Underground Mines?34 citations · 2019
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