22 citations · 46 across the 5 of their papers we have counts for
5 papers
Morphology-Conditioned World Model for Cross-Embodiment Quadrupedal Locomotion
Mohamad H. Danesh, Chenhao Li, Amin Abyaneh +5
World models promise a paradigm shift in robotics, where an agent learns the physics of its environment once and then acquires behaviors efficiently. Yet the learned dynamics model…
Terrain RL Simulator
Glen Berseth, Xue Bin Peng, Michiel van de Panne
We provide challenging simulation environments that range in difficulty. The difficulty of solving a task is linked not only to the number of dimensions in the action space bu…
Feedback Control For Cassie With Deep Reinforcement Learning
Zhaoming Xie, Glen Berseth, Patrick Clary +2
Bipedal locomotion skills are challenging to develop. Control strategies often use local linearization of the dynamics in conjunction with reduced-order abstractions to yield tract…
Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control
Glen Berseth, Cheng Xie, Paul Cernek +1
Deep reinforcement learning has demonstrated increasing capabilities for continuous control problems, including agents that can move with skill and agility through their environmen…
Model-Based Action Exploration for Learning Dynamic Motion Skills
Glen Berseth, Michiel van de Panne
Deep reinforcement learning has achieved great strides in solving challenging motion control tasks. Recently, there has been significant work on methods for exploiting the data gat…