Real-Time Perception Enhancement in Obscured Environments for Underground Mine Search and Rescue Teams

Author:

Demirkan Doga Cagdas1,Segal Ava1,Mallik Abhidipta1,Duzgun Sebnem2,Petruska Andrew J1

Affiliation:

1. Mechanical Engineering Department, Colorado School of Mines, Golden, CO, USA

2. Mining Engineering Department, Colorado School of Mines, Golden, CO, USA

Abstract

First responders in underground mines face a myriad of challenges when searching for personnel in a disaster scenario. Possibly, the most acute challenge is the complete lack of visibility owing to a combination of dust, smoke, and pitch-black conditions. Moreover, the complex environment compounds the difficulty of navigating and searching the area as well as identifying hazardous conditions until in close proximity. Enhanced perception and localization technologies that enable rapid and safe disaster response could mitigate the mine rescue team’s risk and reduce response times. We developed a proof of concept perception enhancement tool for mine rescue personnel in pitch-black conditions by leveraging LiDAR, thermal camera, and data fusion to reconstruct a 3D representation of the space in real-time. This enhancement is visualized on HoloLens, allowing the responders real-time situational awareness of personnel, walls, obstacles, or fires in otherwise opaque environments. The technology is a first step towards faster, safer, and more effective disaster response for mine rescue operations, including detection of unexpected hazards before they become imminent threats.

Publisher

IntechOpen

Reference23 articles.

1. Chen J, Li S, Liu D, Li X. Airobsim: simulating a multisensor aerial robot for urban search and rescue operation and training. Sensors (Switzerland). 2020;20(18):1–20.

2. Beerbower D, Energy P, Biggerstaff R, Coal A, Blackwell WK, Energy C, Mine rescue handbook. USA: University of Michigan; 1961.

3. Bertrand JWM, Fransoo JC. Modelling and simulation. In: Research methods for operations management. New York: Routledge Taylor & Francis Group; 2016. p. 290–330.

4. Zlot R, Bosse M. Efficient large-scale 3D mobile mapping and surface reconstruction of an underground mine. In: Yoshida K, Tadokoro S , editors. Field and Service Robotics: Results of the 8th International Conference [Internet]. Berlin, Heidelberg: Springer; 2014. p. 479–493. Available from: https://doi.org/10.1007/978-3-642-40686-7_32.

5. Conti RS, Chasko LL, Wiehagen WJ, Lazzara CP. Fire response preparedness for underground mines. In: Inf Circ 9481 [Internet]. 2005. 25 p. Available from: https://www.cdc.gov/niosh/mining/UserFiles/works/pdfs/2006-105.pdf.

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