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By M. Salimov, J. Sattarvand

The conventional visualisation method of remote equipment is through the installation of one or more cameras on the machine, and sending a live feed to the operator’s flat display. However, the performance of the teleoperation can be enhanced using better visualisation through virtual reality (VR). This paper presents the process of the design and manufacturing of a robotic platform that will be used in the next phase of the project for a VR-assisted teleoperated excavator. The robot consists of a loading boom and arm arrangement installed on the undercarriage of a CAT300-9D. All hydraulic cylinders are replaced with electric actuators, and crawling motors are substituted by electric motors. The pieces of the boom and the arm, as well as the bucket were designed in Autodesk Inventor, and manufactured from aluminium sheets using a desktop and CNC machine. Parts are joined by pins and welding as needed. An Arduino-based control system is developed for the robot, and motor controllers are used to convert the power commands from the microcontroller to the high-amperage actuators. The control system is capable of communicating with a wireless Play Station controller to operate remotely. The manufactured robotic excavator is planned to be utilised in multiple autonomy research projects.

Sep 1, 2021

By J Westh, S Rashleigh, L Gallagher

Mining companies are moving towards automated haul trucks and other equipment. One reason for this is that if automated trucks can operate in a standard pattern over and over again without variation, then human error is reduced, if not eliminated.The challenge for mining production leaders/managers is to ensure operators follow standard operating procedures for load and dump operations, with each operator doing the same thing, every time. However, operators are only human and inconsistent performance is rife at every mine site. The finger may be pointed at the operators for not doing as instructed. The clarity and variability of trainer instructions may be considered causal to the problem. Herein lies the problem. Almost all operators believe they are following the procedure very closely; moreover, they all demonstrate a strong desire to conform to instruction.Using video analysis and feedback, each operator can be shown where and by how much they differ from the benchmark set by their company. Operators, often for the first time, can see definitively what they are doing, compared to industry best practice.The technology utilised by real-time video (RTV) crews measures time, distance and angles. It can overlay the video of the operator at the load site, with video of the perfect pass. Operators are amazed when they see how near to, or how far they are from best practice.The footage and data gathered by RTV assists operators in understanding exactly what adjustments are required to increase proficiency. It also assists load and dump superintendents to identify where in the process they are losing time. When translated to overburden removal or mineral/resource extraction, the result is large production economies without the need for large capital investment in new automated technology.CITATION:Westh, J, Gallagher, L and Rashleigh, S, 2012. Improving safety and mine productivity using real-time video technology, in Proceedings International Mine Management 2012, pp 173-188 (The Australasian Institute of Mining and Metallurgy: Melbourne).

Nov 20, 2012

By Erik Marsh, Frederick C. Harris Jr., Javad Sattarvand, Joshua Dahl, Alireza Kamran Pishhesari

Based on the mine safety and health administration (MSHA)reports, mining truck accidents are among the significant causes of fatalities in the mining industry. The major causes of haulage accidents can be divided into non-driving and driving factors, such as truck-related sudden failures and operator performance. Numerous parameters affect trucks' safe operation, but situational awareness plays a significant role. Due to the distinct structure of mining trucks, making them efficient for mining purposes, the operator has a very limited field of view (FOV), making them prone to accidents resulting in losing lives. The cabin's position blocks the truck's right and rear sides, creating several blind points around it. Aiming to test/train the operator's awareness of the surrounding, a proximity detection system is developed through a multiplayer virtual reality (VR) application to investigate the human factor in equipment collisions. The operators were examined and monitored when asked to conduct what exactly happened in the Marigold mine truck accident without being aware of the scenario. After receiving sound, vibration, and visual alarm warnings, their reaction and performance were analyzed. The platform is developed using the Unity game engine for HTC VIVE virtual reality goggles. An Omni-direction treadmill and a motion simulator platform are utilized for the player and dump truck operators. Fifteen students were monitored when driving the dump truck receiving/not receiving proximity detection alarms. None of them repeated the accident when receiving proximity alarms. Also, they found the visual alarm the most comfortable while driving the truck.

Jun 25, 2023