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DeepGait: Planning and Control of Quadrupedal Gaits Using Deep Reinforcement Learning.

, , , , and . IEEE Robotics Autom. Lett., 5 (2): 3699-3706 (2020)

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MPC-Net: A First Principles Guided Policy Search., , and . IEEE Robotics Autom. Lett., 5 (2): 2897-2904 (2020)DeepGait: Planning and Control of Quadrupedal Gaits Using Deep Reinforcement Learning., , , , and . IEEE Robotics Autom. Lett., 5 (2): 3699-3706 (2020)Collision-Free MPC for Legged Robots in Static and Dynamic Scenes., , , and . ICRA, page 8266-8272. IEEE, (2021)A Collision-Free MPC for Whole-Body Dynamic Locomotion and Manipulation., , , , and . ICRA, page 4686-4693. IEEE, (2022)Budgeted Knowledge Transfer for State-Wise Heterogeneous RL Agents., , and . ICONIP (1), volume 7663 of Lecture Notes in Computer Science, page 439-446. Springer, (2012)Circus ANYmal: A Quadruped Learning Dexterous Manipulation with Its Limbs., , , , , , , , and . CoRR, (2020)Combining Learning-Based Locomotion Policy With Model-Based Manipulation for Legged Mobile Manipulators., , , , and . IEEE Robotics Autom. Lett., 7 (2): 2377-2384 (2022)Trajectory Optimization Through Contacts and Automatic Gait Discovery for Quadrupeds., , , and . IEEE Robotics Autom. Lett., 2 (3): 1502-1509 (2017)An Efficient Optimal Planning and Control Framework For Quadrupedal Locomotion., , , , and . CoRR, (2016)Combined Sampling and Optimization Based Planning for Legged-Wheeled Robots., , and . ICRA, page 8366-8372. IEEE, (2021)