MineBL: A Battery-Free Localization Scheme with Binocular Camera for Coal Mine

Area of Science:

• Mining Engineering
• Robotics
• Computer Vision

Background:

• Accurate localization in underground coal mines is critical for safety and operational efficiency.
• Existing localization technologies often face challenges related to cost, power, and environmental complexity.

Purpose of the Study:

• To propose a novel, low-cost, battery-free localization scheme for underground coal mines.
• To enhance the accuracy and reliability of target localization in complex subterranean environments.

Main Methods:

• Development of MineBL (Mine Battery-free Localization) system utilizing depth images.
• Implementation of a data enhancement strategy for small-target reorganization to improve position node identification.
• Design of a multi-filter cooperative denoising ranging algorithm and an optimized weighted centroid location algorithm.

Main Results:

• Experimental validation in laboratory and underground coal mine settings.
• Achieved localization errors of less than 30 cm in 95% of cases.
• Demonstrated effective identification of tiny position nodes and minimized localization errors.

Conclusions:

• MineBL offers a promising low-cost and effective solution for precise target localization in underground coal mines.
• The system has significant potential to improve safety and operational management in mining environments.
• The proposed algorithms contribute to advancing localization technologies in challenging subterranean conditions.