6 papers · 1 filter
Shooting for Contact: Contact-Implicit Multiple Shooting for Dynamic Motion Retargeting
Sergio A. Esteban, Jason H. K. Siu, Derrick Mach +4
Motion retargeting approaches often prioritize kinematic similarity over whole-body dynamics, contact consistency, and actuation limits, yielding references that are difficult for…
Accelerating and Scaling MPC-Guided Reinforcement Learning for Humanoid Locomotion and Manipulation
Junheng Li, Liang Wu, Sergio A. Esteban +3
In humanoid motion control, model predictive control (MPC) offers physically grounded prediction and constraint handling, while reinforcement learning (RL) enables robust whole-bod…
On Surprising Effects of Risk-Aware Domain Randomization for Contact-Rich Sampling-based Predictive Control
Sergio A. Esteban, Junheng Li, Vince Kurtz +1
Domain randomization (DR) is widely used in policy learning to improve robustness to modeling error, but remains underexplored in contact-rich sampling-based predictive control (SP…
HALO: Hybrid Auto-encoded Locomotion with Learned Latent Dynamics, Poincaré Maps, and Regions of Attraction
Blake Werner, Sergio A. Esteban, Massimiliano De Sa +2
Reduced-order models are powerful for analyzing and controlling high-dimensional dynamical systems. Yet constructing these models for complex hybrid systems such as legged robots r…
Hierarchical Reduced-Order Model Predictive Control for Robust Locomotion on Humanoid Robots
Adrian B. Ghansah, Sergio A. Esteban, Aaron D. Ames
As humanoid robots enter real-world environments, ensuring robust locomotion across diverse environments is crucial. This paper presents a computationally efficient hierarchical co…
Reduced-Order Model Guided Contact-Implicit Model Predictive Control for Humanoid Locomotion
Sergio A. Esteban, Vince Kurtz, Adrian B. Ghansah +1
Humanoid robots have great potential for real-world applications due to their ability to operate in environments built for humans, but their deployment is hindered by the challenge…