AUTONOMY SENSORS
had this to say : “ In the early days of autonomous mining fleets , vendors chose technologies such as LiDAR or radar because they had proven effective at detecting objects in other applications — even , at times , for the purpose of collision avoidance . The underlying problems these technologies were already solving were not significantly different from those encountered in mining . For use in mining , though , they did need to be ruggedised , fitted , or tuned to function effectively in harsh mining environments .”
However , on working conditions he adds : “ Due to industry-specific problems , technologies that worked in other applications did not perfectly transfer to mining . Cameras used in self-driving cars struggled at minesites due to dust . Milliwave radar developed for cars is tuned to identify ordinary-sized vehicles ; it detects the huge trucks used in mining as multiple vehicles . Previously , there was no LiDAR available that offered both long range and high-resolution data . As a result , AHS needed a strategy other than purely relying on sensors . In many cases , it relied on exchanging vehicle position information with one another . Obviously , this situation is changing as technology evolves .” Other challenges , such as not having road lines , require AHS providers to leverage sensors to detect windrows and berms .
“ For current autonomy systems , the loss of one sensor might result in a stoppage of autonomous operations . Self-cleaning housings and other environmental mitigations , as well as
supplementary maintenance , can help reduce the probability of lost operating hours . In particular , controlling for dust and achieving both long range and high-resolution data have proven major challenges in AHS . While automobiles need to deal with bad weather , dust rarely causes a significant problem , so camera-based systems are common . Since dust is a routine occurrence on mine sites , AHS have to rely on LiDAR and milliwave radar ; however , there are few sensors that can achieve both long range and high-resolution data like cameras . In recent years , third-party companies such as Baraja have emerged , making it possible to use sensors that can deal with dust while also achieving both long range and high-resolution data .”
Politick agreed that GNSS factors heavily in current autonomy solutions for mining , but said it also comes with a challenge : GNSS-powered systems typically stop working if the technology goes offline . Emerging AHSs claim to not rely on any single sensor , including GNSS , for positioning or vehicle safety . Decreased reliance on any one sensor helps improve potential uptime , decreases the impact or need for manual recovery encountered during an outage , and - for GNSS specifically - negates the need for the entire fleet , including light vehicles , to be monitored by high-precision GNSS .”
The mining industry has learned key lessons from automotive and other industries around development of sensors to provide ‘ vision ’ to vehicle command and control - namely the need for a redundant stack of available technologies . “ Likewise , we ’ ve learned to introduce antirutting logic that forces equipment to deviate from their path in order to preserve ground integrity . Mining poses unique challenges from other fields with instrumented vehicles . There are no lines on mine roads . Dust is prevalent . Rutting on roads is a potential issue , and varying degrees of traction are common . Even wellgroomed roads and benches change frequently . Plus , AHS sensors in mining need integration with key operational systems such as the crusher or fleet management system .”
In the automotive industry , vendors have developed drive-assist systems based on cameras and milliwave radar . However , the advent of new , high-performance LiDAR has prompted many of them to steer themselves to autonomous driving based on LiDAR . Similarly , in the mining industry , it is necessary to observe technological progress and assess development trends to determine what technologies may become game changers .
On next steps he comments : “ More sensors and more data can better emulate a driver ’ s instincts and operate the equipment more seamlessly in tandem with manually operated
54 International Mining | SEPTEMBER 2021