1 citations · 2 across the 20 of their papers we have counts for
20 papers
Experimental Characterization of the Passive Mechanical Behavior of Rat Pelvic Floor Muscles: Effects of Test Conditions and Pregnancy
Jose L. Monclova, Matthew Shankel, Ava M. English +2
Purpose: Pelvic floor muscles undergo large deformations during vaginal delivery, yet the passive tensile behavior of pregnant and non-pregnant pelvic floor muscle and the influenc…
Neural-Behavioral Representation of Natural Whole-body Movement in Monkeys
Jieshi He, Puzhe Li, Yanan Sui +1
Understanding how cortical activity represents natural whole-body behaviors in primates remains challenging. Limited by the diversity of movements and inaccessibility of large-scal…
MyoChallenge 2025: A New Benchmark for Human Athletic Intelligence
Cheryl Wang, Chun Kwang Tan, Balint K. Hodossy +21
Athletic performance represents the pinnacle of human motor intelligence, demanding rapid choices, precise control, agility, and coordinated physical execution. Replicating this se…
Scaling Whole-Body Human Musculoskeletal Behavior Emulation for Specificity and Diversity
Yunyue Wei, Chenhui Zuo, Shanning Zhuang +3
The embodied learning of human motor control requires whole-body neuro-actuated musculoskeletal dynamics, while the internal muscle-driven processes underlying movement remain inac…
Embodied Human Simulation for Quantitative Design and Analysis of Interactive Robotics
Chenhui Zuo, Jinhao Xu, Michael Qian Vergnolle +1
Physical interactive robotics, ranging from wearable devices to collaborative humanoid robots, require close coordination between mechanical design and control. However, evaluating…
Whole-Brain Connectomic Graph Model Enables Whole-Body Locomotion Control in Fruit Fly
Zehao Jin, Yaoye Zhu, Chen Zhang +1
Animals perform coordinated whole-body movements under the control of neural systems shaped by brain-wide connectivity. The mapping of the whole-brain neural connections, or the co…
Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
Yunyue Wei, Chenhui Zuo, Yanan Sui
Controlling high-dimensional systems in biological and robotic applications is challenging due to expansive state-action spaces, where effective exploration is critical. Commonly u…
Embodied Learning of Reward for Musculoskeletal Control with Vision Language Models
Saraswati Soedarmadji, Yunyue Wei, Chen Zhang +2
Discovering effective reward functions remains a fundamental challenge in motor control of high-dimensional musculoskeletal systems. While humans can describe movement goals explic…
Energy-Efficient Omnidirectional Locomotion for Wheeled Quadrupeds via Predictive Energy-Aware Nominal Gait Selection
Xu Yang, Wei Yang, Kaibo He +3
Wheeled-legged robots combine the efficiency of wheels with the versatility of legs, but face significant energy optimization challenges when navigating diverse environments. In th…
Contact-Rich and Deformable Foot Modeling for Locomotion Control of the Human Musculoskeletal System
Haixin Gong, Chen Zhang, Yanan Sui
The human foot serves as the critical interface between the body and environment during locomotion. Existing musculoskeletal models typically oversimplify foot-ground contact mecha…
Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations
Chengtian Ma, Yunyue Wei, Chenhui Zuo +2
Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of stati…
Human sensory-musculoskeletal modeling and control of whole-body movements
Chenhui Zuo, Guohao Lin, Chen Zhang +2
Coordinated human movement depends on the integration of multisensory inputs, sensorimotor transformation, and motor execution, as well as sensory feedback resulting from body-envi…
Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
Yunyue Wei, Shanning Zhuang, Vincent Zhuang +1
Controlling high-dimensional nonlinear systems, such as those found in biological and robotic applications, is challenging due to large state and action spaces. While deep reinforc…
Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems
Yunyue Wei, Zeji Yi, Hongda Li +2
Learning to move is a primary goal for animals and robots, where ensuring safety is often important when optimizing control policies on the embodied systems. For complex tasks such…
Scalable Bayesian Optimization via Focalized Sparse Gaussian Processes
Yunyue Wei, Vincent Zhuang, Saraswati Soedarmadji +1
Bayesian optimization is an effective technique for black-box optimization, but its applicability is typically limited to low-dimensional and small-budget problems due to the cubic…
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma +1
Learning an effective policy to control high-dimensional, overactuated systems is a significant challenge for deep reinforcement learning algorithms. Such control scenarios are oft…
Distributionally Robust Constrained Reinforcement Learning under Strong Duality
Zhengfei Zhang, Kishan Panaganti, Laixi Shi +3
We study the problem of Distributionally Robust Constrained RL (DRC-RL), where the goal is to maximize the expected reward subject to environmental distribution shifts and constrai…
Improving sample efficiency of high dimensional Bayesian optimization with MCMC
Zeji Yi, Yunyue Wei, Chu Xin Cheng +2
Sequential optimization methods are often confronted with the curse of dimensionality in high-dimensional spaces. Current approaches under the Gaussian process framework are still…
An Invariant Information Geometric Method for High-Dimensional Online Optimization
Zhengfei Zhang, Yunyue Wei, Yanan Sui
Sample efficiency is crucial in optimization, particularly in black-box scenarios characterized by expensive evaluations and zeroth-order feedback. When computing resources are ple…
Self Model for Embodied Intelligence: Modeling Full-Body Human Musculoskeletal System and Locomotion Control with Hierarchical Low-Dimensional Representation
Chenhui Zuo, Kaibo He, Jing Shao +1
Modeling and control of the human musculoskeletal system is important for understanding human motor functions, developing embodied intelligence, and optimizing human-robot interact…