Robotic Vision for Space Mining. (arXiv:2109.12109v1 [cs.RO])

Future Moon bases will likely be constructed using resources mined from the
surface of the Moon. The difficulty of maintaining a human workforce on the
Moon and communications lag with Earth means that mining will need to be
conducted using collaborative robots with a high degree of autonomy. In this
paper, we explore the utility of robotic vision towards addressing several
major challenges in autonomous mining in the lunar environment: lack of
satellite positioning systems, navigation in hazardous terrain, and delicate
robot interactions. Specifically, we describe and report the results of robotic
vision algorithms that we developed for Phase 2 of the NASA Space Robotics
Challenge, which was framed in the context of autonomous collaborative robots
for mining on the Moon. The competition provided a simulated lunar environment
that exhibits the complexities alluded to above. We show how machine
learning-enabled vision could help alleviate the challenges posed by the lunar
environment. A robust multi-robot coordinator was also developed to achieve
long-term operation and effective collaboration between robots.



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