7 citations · 8 across the 10 of their papers we have counts for
5 papers · 1 filter
Inertially Significant Humanoid Teleoperation via Whole Body Model Predictive Control and Online Parameter Estimation
James Foster, Beomyeong Park, Luigi Penco +1
The effective deployment of humanoid robots in practical tasks of interest will require a capability of sensing and adapting to variations in inertial parameters, as occurs during…
Reactive Humanoid Multi-Contact Using Learned Stability Models
Stephen McCrory, Beomyeong Park, Nicholas Kitchel +2
We present a planning and control approach to reactively use hand contacts to stabilize a humanoid in low stability scenarios, where only using feet contacts may result in a fall.…
A System for Fast, Resilient, and Adaptable Loco-Manipulation Behaviors on Humanoid Robots
Duncan Calvert, Luigi Penco, Dexton Anderson +4
There is tremendous value in humanoid robots taking on physically demanding, hazardous, and repetitive work in spaces built for humans. However, a useful robot for these spaces mus…
HANDOFF: Humanoid Agentic Task-Space Whole-Body Control via Distilled Complementary Teachers
Lizhi Yang, Junheng Li, Nehar Poddar +5
Humanoid loco-manipulation benefits from one controller to coordinate locomotion, arm movements, and fall recovery. These behaviors are difficult to learn together from scratch bec…
Embedding Classical Balance Control Principles in Reinforcement Learning for Humanoid Recovery
Nehar Poddar, Stephen McCrory, Luigi Penco +3
Humanoid robots remain vulnerable to falls and unrecoverable failure states, limiting their practical utility in unstructured environments. While reinforcement learning has demonst…