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 threedimensional reorientation and landing of a quadruped robot exploring lowgravity celestial bodies. Using simtoreal transfer, we deploy trained policies in the real world on the SpaceBok robot placed on an experimental testbed designed for twodimensional microgravity experiments. Title: Catlike Jumping and Landing of Legged Robots in Lowgravity 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 4812016. For more information visit:
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