New technology for tracking autonomous mining vehicles

Posted Dec 31, 2017 by Tim Sandle
Researchers have used new technology, based on robotics, to track and assess the status of autonomous underground mining vehicles.
Underground Mining
A shot of the mining operation at the Bachelor Lake Mine.
Metanor Resources, Inc.
The robotics researchers, based at Queensland University of Technology, have developed a new technology designed to equip underground mining vehicles so they can navigate autonomously through dust, camera blur and bad lighting. These types of hazards normally render a mining vehicle non-operational.
The researchers have achieved this new level of control through a combination of mathematics and biologically-inspired algorithms. The new technology makes use of vehicle-mounted cameras. The cameras function to track the location of the vehicle in underground tunnels to within a few meters.
Autonomous vehicles are commonly being used in the global underground mining industry. One driver for this is because machinery s required so that mining companies can navigate through harsh environment and maze of tunnels. While machinery has advanced it continues to have limitations in the face of the harsh conditions underground, which was the motivation for the new research.
The video below shows the researchers and vehicles in action:
The aim of the new technology was to improve vehicle sensing through infrastructure modifications and to develop new positioning technology to increases efficiency and safety underground. With the development the researchers constructed a different type of positioning system that relies upon cameras rather than lasers. Underground, conventional Global Positioning Systems cannot be used and Wireless Sensor Networks have proved to be unreliable.
The research was conducted at the university's Australian Centre for Robotic Vision, led by Professor Michael Milford. The research was undertaken in collaboration with Catepillar, Mining together with funding provided by the Queensland Government. The next phase of the research is to incorporate artificial intelligence into the camera technology.