Localisation of mobile underground mining equipment using wireless ethernet

Ralston, Jonathon; Hargrave, Chad; Hainsworth, D.W.

doi:10.1109/ias.2005.1518314

Cited by 22 publications

(15 citation statements)

References 4 publications

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“…• Employing radio frequency identification (RFID) tags for event-based tracking of equipment and personnel [115] • Use of radio signals (e.g., installed Wi-Fi access points) for signal strength-based positioning [116,117], which is very difficult in underground mines due to severe multipath and shadowing, as well as non-line-of sigh propagation and the need for too many devices in order to obtain GPS-like accuracies…”

Section: Underground Positioning and Trackingmentioning

confidence: 99%

Robotics in Mining

Marshall

Bonchis

Nebot

et al. 2016

Springer Handbook of Robotics

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This chapter presents an overview of the state-of-the-art in mining robotics, from surface to underground applications, and beyond. Mining is the practice of extracting resources for utilitarian purposes. Today, the international business of mining is a heavily mechanized industry that exploits the use of large diesel and electric equipment. These machines must operate in harsh, dynamic, and uncertain environments such as, for example, in the high arctic, in extreme desert climates, and in deep underground tunnel networks where it can be very hot and humid. Applications of robotics in mining are broad and include robotic dozing, excavation, and haulage, robotic mapping and surveying, as well as robotic drilling and explosives handling. This chapter describes how many of these applications involve unique technical challenges for field roboticists. However, there are compelling reasons to advance the discipline of mining robotics, which include not only a desire on the part of miners to improve productivity, safety, and lower costs, but also out of a need to meet product demands by accessing orebodies situated in increasingly challenging conditions.

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Section: Underground Positioning and Trackingmentioning

confidence: 99%

Robotics in Mining

Marshall

Bonchis

Nebot

et al. 2016

Springer Handbook of Robotics

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“…They conduct tests in two kinds of tunnels and conclude that the accuracy of such a system would be within 20 metres. In [14], the authors announce a precision of 5 to 15 metres with a Wi-Fibased positioning system, but the experiments did not take place in an actual mine; this system uses a different positioning technique, since it uses a manually-calibrated, mobile-centred fingerprint of the signal strength. A similar technique is used in [15] for location-based services in subway stations.…”

Section: Related Workmentioning

confidence: 99%

Wi-Fi-based Positioning in a Complex Underground Environment

Cypriani

Delisle²,

Hakem³

2015

JNW

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Underground mining tunnels constitute a very particular environment for radio wave propagation-with characteristics of both indoor and outdoor "regular" environments. This paper shows how a general-purpose Wi-Fi-based indoor positioning system, OwlPS (Owl Positioning System) was adapted to work in that particular environment. A series of experiments, conducted in a formerly exploited gold mine at 70 metres below the surface, across about 400 metres of drifts, is then introduced; it primarily aims at determining the positioning accuracy that can be reached in such a context with a Wi-Fi-based positioning system using the signal strength at 2.4 GHz. The results obtained are improved with a filter, and the mean Euclidean distance error is under 10 metres in most cases when the terminal is carried by an operator; this makes OwlPS usable as is for asset management and emergency positioning of workers underground.

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“…Commonwealth Scientific and Industrial Research Organisation (CSIRO) Exploration and Mining in Australia has taken the lead in wireless technologies for localization of mobile equipment operating in an underground coal mining environment [Ralston et al 2005]. CSIRO research involves the use of IEEE 802.11b Wireless Ethernet and uses the signal strength received from several wireless access points for the real-time localization.…”

Section: Related Researchmentioning

confidence: 99%