The paper Large Batch Simulation for Deep Reinforcement Learning was accepted to the International Conference on Learning Representations (ICLR).
Paper published in Science Robotics and featured on the cover
Posted on October 22, 2020
Learning Quadrupedal Locomotion over Challenging Terrain was published in Science Robotics and featured on the journal’s cover. The paper presents a radically robust legged locomotion controller for rough terrain and demonstrates remarkable zero-shot generalization from simulation to natural environments. The controller retains its robustness under conditions that have never been encountered during training: deformable terrain such as mud and snow, dynamic footholds such as rubble, and overground impediments such as thick vegetation and gushing water.