Papers
4
Total Citations
19
H-Index
3
About
Yueqi Bi is an emerging researcher specializing in underground coal mine automation, autonomous robotics, and indoor positioning systems — a technically demanding field where conventional technologies routinely fail. Working at the intersection of robotics, navigation, and mining engineering, Bi has focused on solving critical safety and operational challenges in one of the world's most hazardous industrial environments. Bi's most recognized contribution, "Research on Location Estimation for Coal Tunnel Vehicle Based on Ultra-Wide Band Equipment" (2022, 11 citations), addresses the fundamental problem of GPS-denied positioning in underground roadways, where dust, water mist, uneven surfaces, and poor lighting render standard navigation approaches unreliable. This work established Bi as a thoughtful innovator in subterranean localization. Subsequent research expanded into the design and control of Mining Trackless Auxiliary Transportation Robots (MTATBOTs), exploring odometer-assisted inertial measurement for autonomous driving, four-wheel steering stability via PID control, and fully integrated unmanned material distribution systems. Together, these contributions represent a coherent research program aimed at reducing human labor intensity and accident rates in underground coal mine logistics. With 19 cumulative citations across four papers spanning just three years, Bi demonstrates steady and promising scholarly momentum in an operationally vital domain.
Research Focus
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