10.1k citations · 12.2k across the 20 of their papers we have counts for
7 papers · 1 filter
Whole-Body Model-Predictive Control of Legged Robots with MuJoCo
John Z. Zhang, Taylor A. Howell, Zeji Yi +6
We demonstrate the surprising real-world effectiveness of a very simple approach to whole-body model-predictive control (MPC) of quadruped and humanoid robots: the iterative LQR (i…
Efficient Online Learning of Contact Force Models for Connector Insertion
Kevin Tracy, Zachary Manchester, Ajinkya Jain +4
Contact-rich manipulation tasks with stiff frictional elements like connector insertion are difficult to model with rigid-body simulators. In this work, we propose a new approach f…
Language to Rewards for Robotic Skill Synthesis
Wenhao Yu, Nimrod Gileadi, Chuyuan Fu +17
Large language models (LLMs) have demonstrated exciting progress in acquiring diverse new capabilities through in-context learning, ranging from logical reasoning to code-writing.…
Predictive Sampling: Real-time Behaviour Synthesis with MuJoCo
Taylor Howell, Nimrod Gileadi, Saran Tunyasuvunakool +3
We introduce MuJoCo MPC (MJPC), an open-source, interactive application and software framework for real-time predictive control, based on MuJoCo physics. MJPC allows the user to ea…
dm_control: Software and Tasks for Continuous Control
Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal +8
The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A MuJoCo wrapper provides c…
Modelling Generalized Forces with Reinforcement Learning for Sim-to-Real Transfer
Rae Jeong, Jackie Kay, Francesco Romano +6
Learning robotic control policies in the real world gives rise to challenges in data efficiency, safety, and controlling the initial condition of the system. On the other hand, sim…