A brand new computer model mimics Moon dust so well that it may lead to smoother and safer Lunar robot teleoperations.
The tool, developed by researchers on the University of Bristol and based on the Bristol Robotics Laboratory, may very well be used to coach astronauts ahead of Lunar missions.
Working with their industry partner, Thales Alenia Space within the UK, who has specific interest in creating working robotic systems for space applications, the team investigated a virtual version of regolith, one other name for Moon dust.
Lunar regolith is of particular interest for the upcoming Lunar exploration missions planned over the subsequent decade. From it, scientists can potentially extract priceless resources equivalent to oxygen, rocket fuel or construction materials, to support a long-term presence on the Moon.
To gather regolith, remotely operated robots emerge as a practical selection attributable to their lower risks and costs in comparison with human spaceflight. Nevertheless, operating robots over these large distances introduces large delays into the system, which make them harder to manage.
Now that the team know this simulation behaves similarly to reality, they will use it to mirror operating a robot on the Moon. This approach allows operators to manage the robot without delays, providing a smoother and more efficient experience.
Lead creator Joe Louca, based in Bristol’s School of Engineering Mathematics and Technology explained: “Consider it like a sensible video game set on the Moon — we wish to make sure that the virtual version of moon dust behaves identical to the actual thing, in order that if we’re using it to manage a robot on the Moon, then it should behave as we expect.
“This model is accurate, scalable, and light-weight, so will be used to support upcoming lunar exploration missions.”
This study followed from previous work of the team, which found that expert robot operators need to train on their systems with progressively increasing risk and realism. Meaning starting in a simulation and build up to using physical mock-ups, before moving on to using the actual system. An accurate simulation model is crucial for training and developing the operator’s trust within the system.
While some especially accurate models of Moon dust had previously been developed, these are so detailed that they require a variety of computational time, making them too slow to manage a robot easily. Researchers from DLR (German Aerospace Centre) tackled this challenge by developing a virtual model of regolith that considers its density, stickiness, and friction, in addition to the Moon’s reduced gravity. Their model is of interest for the space industry because it is light on computational resources, and, hence, will be run in real-time. Nevertheless, it really works best with small quantities of Moon dust.
The Bristol team’s goals were to, firstly, extend the model so it will possibly handle more regolith, while staying lightweight enough to run in real-time, after which to confirm it experimentally.
Joe Louca added: “Our primary focus throughout this project was on enhancing the user experience for operators of those systems — how could we make their job easier?
“We began with the unique virtual regolith model developed by DLR, and modified it to make it more scalable.
“Then, we conducted a series of experiments — half in a simulated environment, half in the true world — to measure whether the virtual moon dust behaved the identical as its real-world counterpart.”
As this model of regolith is promising for being accurate, scalable and light-weight enough to be utilized in real-time, the team will next investigate whether it will possibly be used when operating robots to gather regolith.
In addition they plan to analyze whether the same system may very well be developed to simulate Martian soil, which may very well be of profit for future exploration missions, or to coach scientists to handle material from the highly anticipated Mars Sample Return mission.
