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A navigation system for automated loaders in underground mines
Örebro University, Department of Technology. (Mobile Robotics Lab)
Örebro University, Department of Technology. (Mobile Robotics Lab)
Örebro University, Department of Technology. (Mobile Robotics Lab)ORCID iD: 0000-0001-8229-1363
2006 (Swedish)In: Field and Service Robotics: results of the 5th international conference / [ed] Peter Corke, Salah Sukkariah, Berlin: Springer Berlin/Heidelberg, 2006, p. 129-140Conference paper, Published paper (Refereed)
Abstract [en]

For underground mining operations human operated LHD vehicles are typically used for transporting ore. Because of security issues and of the cost of human operators, alternative solutions such as tele-operated vehicles are often in use. Tele-operation, however, leads to reduced efficiency, and it is not an ideal solution. Full automation of the LHD vehicles is a challenging task, which is expected to result in increased operational efficiency, cost efficiency, and safety. In this paper, we present our approach to a fully automated solution currently under development. We use a fuzzy behavior-based approach for navigation, and develop a cheap and robust localization technique based on the deployment of inexpensive passive radio frequency identification (RFID) tags at key points in the mine.

Place, publisher, year, edition, pages
Berlin: Springer Berlin/Heidelberg, 2006. p. 129-140
Series
Springer tracts in advanced robotics, ISSN 1610-7438 ; 25
Keywords [en]
Mining vehicles, fuzzy logic, hybrid maps, behavior-based navigation, autonomous robots, RFID
National Category
Computer and Information Sciences Robotics
Research subject
Computer and Systems Science
Identifiers
URN: urn:nbn:se:oru:diva-3603DOI: 10.1007/978-3-540-33453-8ISBN: 978-3-540-33453-8 (print)OAI: oai:DiVA.org:oru-3603DiVA, id: diva2:137901
Conference
5th international conference on Field and service robotics (FSR), July 29 - 31, 2005. Port Douglas, Australia
Available from: 2007-07-22 Created: 2007-07-22 Last updated: 2018-01-13Bibliographically approved
In thesis
1. Unmanned operation of load-haul-dump vehicles in mining environments
Open this publication in new window or tab >>Unmanned operation of load-haul-dump vehicles in mining environments
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Underground mines typically do not represent the best working conditions for humans, and many mining companies have the intent to remove all humans from the ore extraction areas. To achieve this goal automation of the mining machinery is required. One of the riskier jobs in a mine is to operate the Load-Haul-Dump (LHD) vehicles that are used to transport the ore from the blast site to a truck, lorry or directly to a crusher. Today these vehicles are typically controlled by an on-board manual operator. The purpose of the work presented in this thesis is to develop and evaluate algorithms and methods to enable high productivity unmanned operation of LHDs, including two different operating modes.

The first mode is fully autonomous navigation, applicable to static environments, where the LHDs are repeatedly driven along the same paths for extended periods. Here, an existing framework for reactive navigation based on fuzzy logic has been extended with novel feature detection algorithms for tunnel following and topological localisation based on 2D laser range scanner data. These algorithms have been verified in quantitative tests to be fast, reliable and tolerant to noise in the sensor data. Moreover, the whole navigation system has been evaluated in qualitative tests in indoor environments using an ordinary research robot. The autonomous navigation system for LHDs currently commercialized by Atlas Copco is partly based on the experiences gained from the work presented here.

The second mode explored is semi-autonomous operation, where local-autonomy functionality on-board the machine assists a tele-remote operator in driving the vehicle along a collision-free path. This mode is intended for mines where the driving path of the machine changes frequently, so the setup needed for a fully autonomous system becomes impractical. In this part of the work a user study in a real mine has been performed, showing that local autonomy has the potential to significantly improve the productivity of a tele-remote operated LHD. Based on these results, a commercial tele-operating system for underground mines has been extended with a novel local autonomy functionality, inspired by existing autonomous navigation systems. The performance of this system has been verified in experiments performed on a real 38 tonnes LHD in a test mine, and in simulations aimed to show that the system works in arbitrary underground mine environments.

Place, publisher, year, edition, pages
Örebro: Örebro university, 2011. p. 51
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 51
National Category
Computer and Information Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-22264 (URN)
Public defence
2011-12-14, Hörsal T, Örebro universitet, Fakultetsgatan 1, Örebro, 13:15 (Swedish)
Opponent
Supervisors
Note
Prof. Alessandro Saffiotti is a member of Centre for Applied Autonomous Sensor Systems (AASS) , Örebro UniversityAvailable from: 2012-03-28 Created: 2012-03-28 Last updated: 2018-01-12Bibliographically approved

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Publisher's full texthttp://www.aass.oru.se/Research/Robots/publications.html

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Larsson, JohanBroxvall, MathiasSaffiotti, Alessandro

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