Automation of an underground mining vehicle using reactive navigation and opportunistic localization

This paper describes the implementation of an autonomous navigation system onto a 30 tonne Load-Haul-Dump truck. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made - a technique we refer to as opportunistic localization. The truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Reactive navigation and opportunistic localization for autonomous underground mining vehicles

This paper describes an autonomous navigation system for a large underground mining vehicle. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made – a technique we refer to as opportunistic localization. The paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Symptoms of heat illness in surface mine workers

Objective: To assess the symptoms of heat illness experienced by surface mine workers. Methods: Ninety-one surface mine workers across three mine sites in northern Australia completed a heat stress questionnaire evaluating their symptoms for heat illness. A cohort of 56 underground mine workers also participated for comparative purposes. Participants were allocated into asymptomatic, minor or moderate heat illness categories depending on the number of symptoms they reported. Participants also reported the frequency of symptom experience, as well as their hydration status (average urine colour). Results: Heat illness symptoms were experienced by 87 and 79 % of surface and underground mine workers, respectively (p = 0.189), with 81–82 % of the symptoms reported being experienced by miners on more than one occasion. The majority (56 %) of surface workers were classified as experiencing minor heat illness symptoms, with a further 31 % classed as moderate; 13 % were asymptomatic. A similar distribution of heat illness classification was observed among underground miners (p = 0.420). Only 29 % of surface miners were considered well hydrated, with 61 % minimally dehydrated and 10 % significantly dehydrated, proportions that were similar among underground miners (p = 0.186). Heat illness category was significantly related to hydration status (p = 0.039) among surface mine workers, but only a trend was observed when data from surface and underground miners was pooled (p = 0.073). Compared to asymptomatic surface mine workers, the relative risk of experiencing minor and moderate symptoms of heat illness was 1.5 and 1.6, respectively, when minimally dehydrated. Conclusions: These findings show that surface mine workers routinely experience symptoms of heat illness and highlight that control measures are required to prevent symptoms progressing to medical cases of heat exhaustion or heat stroke.

Evaluation of internal navigation sensor suites for underground mining vehicle navigation

This paper describes a series of trials that were done at an underground mine in New South Wales, Australia. Experimental results are presented from the data obtained during the field trials and suitable sensor suites for an autonomous mining vehicle navigation system are evaluated.

Autonomous control of underground mining vehicles using reactive navigation

Describes how many of the navigation techniques developed by the robotics research community over the last decade may be applied to a class of underground mining vehicles (LHDs and haul trucks). We review the current state-of-the-art in this area and conclude that there are essentially two basic methods of navigation applicable. We describe an implementation of a reactive navigation system on a 30 tonne LHD which has achieved full-speed operation at a production mine.

Automation of underground truck haulage

This paper reviews the state-of-the art in the automation of underground truck haulage. Past attemps at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tram...

Automation of underground truck haulage

This paper reviews the state-of-the-art in the automation of underground truck haulage. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tramming systems currently being commercialised, that follow rail-type guides placed along the back, cannot match the performance, flexibility and reliability of systems based on modern mobile robotic principles. In addition, the lack of collision detection research in the underground environment is highlighted.

The Application of wireless LANS in mine automation

The objective of this paper is to provide an overview of mine automation applications, developed at the Queensland Centre for Advanced Technology (QCAT), which make use of IEEE 802.11b wireless local area networks (WLANs). The paper has been prepared for a 2002 conference entitled "Creating the Virtual Enterprise - Leveraging wireless technology within existing business models for corporate advantage". Descriptions of the WLAN components have been omitted here as such details are presented in the accompanying papers. The structure of the paper is as follows. Application overviews are provided in Sections 2 to 7. Some pertinent strengths and weaknesses are summarised in Section 8. Please refer to http://www.mining-automation.com/ or contact the authors for further information.