Cat-like Jumping and Landing of Legged Robots in Low-gravity

We show that deep reinforcement learning can be used to learn policies for legged locomotion control tasks encountered in space exploration. such as three-dimensional re-orientation and landing of a quadruped robot exploring low-gravity celestial bodies. Using sim-to-real transfer, we deploy trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for two-dimensional micro-gravity experiments. Title: Cat-like Jumping and Landing of Legged Robots in Low-gravity Using Deep Reinforcement Learning Authors: Nikita Rudin, Hendrik Kolvenbach, Vassilios Tsounis and Marco Hutter IEEE Transactions on Robotics (Early Access): DOI: Also available here: This work was supported by the European Space Agency (ESA) and Airbus DS in the framework of the Network Partnering Initiative 481-2016. For more informati