Search Results for author: Jonathan Hurst

Found 4 papers, 2 papers with code

Sim-to-Real Learning for Bipedal Locomotion Under Unsensed Dynamic Loads

no code implementations9 Apr 2022 Jeremy Dao, Kevin Green, Helei Duan, Alan Fern, Jonathan Hurst

We show that prior RL policies trained for unloaded locomotion fail for some loads and that simply training in the context of loads is enough to result in successful and improved policies.

Sim-to-Real Learning of All Common Bipedal Gaits via Periodic Reward Composition

no code implementations2 Nov 2020 Jonah Siekmann, Yesh Godse, Alan Fern, Jonathan Hurst

We study the problem of realizing the full spectrum of bipedal locomotion on a real robot with sim-to-real reinforcement learning (RL).

Robotics

Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie

1 code implementation22 Mar 2019 Zhaoming Xie, Patrick Clary, Jeremy Dao, Pedro Morais, Jonathan Hurst, Michiel Van de Panne

Deep reinforcement learning (DRL) is a promising approach for developing legged locomotion skills.

Robotics

Feedback Control For Cassie With Deep Reinforcement Learning

3 code implementations15 Mar 2018 Zhaoming Xie, Glen Berseth, Patrick Clary, Jonathan Hurst, Michiel Van de Panne

By formulating a feedback control problem as finding the optimal policy for a Markov Decision Process, we are able to learn robust walking controllers that imitate a reference motion with DRL.

Robotics

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