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Houcheng Li

7 accepted papers

2026

Motion Adaptation for Exoskeletons Across Users and Tasks via Meta-Learning

RA-L 2026

Wearable exoskeletons can augment human strength and reduce muscle fatigue during specific tasks. However, developing personalized and task-generalizable assistance algorithms remains a critical challenge. To address this, a meta-imitation learning approach is proposed. This approach leverages a tas

Cited by 0SourceScholar
2025

Design and Performance Analysis of a Series-Parallel Self-Aligning Index Finger Exoskeleton

RA-L 2025

Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while pro

Cited by 0SourceScholar
2025

EIC Framework for Hand Exoskeletons Based on a Multimodal Large Language Model

IROS 2025

Current hand exoskeleton interaction methods primarily focus on recognizing a limited range of hand motion intentions and rely on pre-programmed control to execute predefined commands. However, these approaches face significant limitations when confronted with unanticipated or non-predefined scenari

Cited by 1SourceScholar
2025

Neural-Lyapunov Fusion: Stable Dynamical System Learning for Robotic Motion Generation

IROS 2025

Point-to-point and periodic motions are ubiquitous in the world of robotics. To master these motions, Autonomous Dynamic System (ADS) based algorithms are fundamental in the domain of Learning from Demonstration (LfD). However, these algorithms face the significant challenge of balancing precision i

Cited by 0SourceScholar
2025

Voluntary Control of the Hand Assistive Exoskeleton Based on the sEMG-Driven Musculoskeletal Model

RA-L 2025

This paper presents a novel voluntary control method for a hand assistive exoskeleton, leveraging an sEMG-driven musculoskeletal model to improve the performance of grasping tasks. To address the challenge of inadequate personalization in current hand exoskeleton assistance strategies, this research

Cited by 5SourceScholar
2024

Learning a Stable Dynamic System with a Lyapunov Energy Function for Demonstratives Using Neural Networks

ICRA 2024poster

Autonomous Dynamic System (DS)-based algorithms hold a pivotal and foundational role in the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable challenge of striking a delicate balance between achieving precision in learning and ensuring the overall stability of th…

Cited by 2SourceScholar