Minhan Li

College of Engineering

Works (10)

Updated: July 31st, 2023 21:16

2023 journal article

Hierarchical Optimization for Control of Robotic Knee Prostheses Toward Improved Symmetry of Propulsive Impulse

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 70(5), 1634–1642.

By: M. Li n, W. Liu, J. Si*, J. Stallrich n & H. Huang n 

Contributors: M. Li n, W. Liu, J. Si*, J. Stallrich n & H. Huang n 

author keywords: Prosthetics; Knee; Robots; Legged locomotion; Kinematics; Optimization; Impedance; Human-in-the-loop; Bayesian optimization; reinforcement learning; gait symmetry; robotic prostheses
MeSH headings : Humans; Knee Prosthesis; Robotics; Robotic Surgical Procedures; Gait; Walking; Knee Joint / surgery; Biomechanical Phenomena
TL;DR: This work proposes a novel hierarchical framework to personalize robotic knee prosthesis control and improve overall gait performance and shows that the design successfully shaped the target knee kinematics as well as configured 12 impedance control parameters to improve propulsive impulse symmetry of the human users. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: March 15, 2023

2022 journal article

Fusion of Human Gaze and Machine Vision for Predicting Intended Locomotion Mode

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 30, 1103–1112.

By: M. Li n, B. Zhong n , E. Lobaton n  & H. Huang n 

Contributors: M. Li n, B. Zhong n , E. Lobaton n  & H. Huang n 

author keywords: Wearable robots; Feature extraction; Point cloud compression; Machine vision; Cameras; Legged locomotion; Visualization; Human gaze; machine vision; intent recognition; wearable robot; deep learning
MeSH headings : Algorithms; Humans; Intention; Locomotion; Lower Extremity; Walking
TL;DR: A novel system that fuses the human gaze and machine vision for locomotion intent recognition of lower limb wearable robots is developed, showing high accuracy of intent recognition and reliable decision-making on locomotion transition with adjustable lead time. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: May 4, 2022

2022 journal article

Reinforcement Learning Impedance Control of a Robotic Prosthesis to Coordinate With Human Intact Knee Motion

IEEE ROBOTICS AND AUTOMATION LETTERS, 7(3), 7014–7020.

By: R. Wu *, M. Li n, Z. Yao *, W. Liu n, J. Si* & H. Huang n 

Contributors: R. Wu *, M. Li n, Z. Yao *, W. Liu n, J. Si* & H. Huang n 

author keywords: Reinforcement learning; prosthetics and exoskeletons; compliance and impedance control; physical human-robot interaction
TL;DR: By formulating the “echo control” of the robotic knee as a reinforcement learning problem, this paper provides a promising new tool for real-time tracking control design without explicitly representing the underlying dynamics using a mathematical model, which can be difficult to obtain for a human-robot system. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: June 27, 2022

2021 article

A Data-Driven Reinforcement Learning Solution Framework for Optimal and Adaptive Personalization of a Hip Exoskeleton

2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021), pp. 10610–10616.

By: X. Tu  n, M. Li n, M. Liu n, J. Si * & H. Huang n 

Contributors: X. Tu  n, M. Li n, M. Liu n, J. Si * & H. Huang n 

author keywords: Exoskeleton; reinforcement learning; optimal adaptive control; least square policy iteration; data driven
TL;DR: The results showed that the optimal and adaptive RL controller as a new approach was feasible for tuning assistive torque profile of the hip exoskeleton that coordinated with human actions and reduced activation level of hip extensor muscle in human. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: November 21, 2021

2021 journal article

Environmental Context Prediction for Lower Limb Prostheses With Uncertainty Quantification

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 18(2), 458–470.

By: B. Zhong n , R. Silva  n, M. Li n, H. Huang n  & E. Lobaton n 

Contributors: B. Zhong n , R. Silva  n, M. Li n, H. Huang n  & E. Lobaton n 

author keywords: Uncertainty; Neural networks; Bayes methods; Measurement uncertainty; Cameras; Microsoft Windows; Bayesian neural network (BNN); environmental context prediction; prosthesis; uncertainty quantification
TL;DR: A novel vision-based context prediction framework for lower limb prostheses to simultaneously predict human’s environmental context for multiple forecast windows by leveraging the Bayesian neural networks (BNNs) and producing a calibrated predicted probability for online decision-making. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: May 28, 2020

2021 article

Reinforcement Learning Control of Robotic Knee With Human-in-the-Loop by Flexible Policy Iteration

Gao, X., Si, J., Wen, Y., Li, M., & Huang, H. (2021, May 6). IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, Vol. 5.

By: X. Gao *, J. Si*, Y. Wen n, M. Li n & H. Huang n 

Contributors: X. Gao *, J. Si*, Y. Wen n, M. Li n & H. Huang n 

author keywords: Robots; Impedance; Tuning; Prosthetics; Knee; Erbium; Legged locomotion; Adaptive optimal control; data- and time-efficient learning; flexible policy iteration (FPI); human-in-the-loop; reinforcement learning (RL); robotic knee
MeSH headings : Humans; Computer Simulation; Neural Networks, Computer; Policy; Robotic Surgical Procedures; Robotics
TL;DR: This study introduces flexible policy iteration (FPI), which can flexibly and organically integrate experience replay and supplemental values from prior experience into the RL controller, and shows system-level performances, including convergence of the approximate value function, (sub)optimality of the solution, and stability of the system. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: October 18, 2021

2021 journal article

Taking both sides: seeking symbiosis between intelligent prostheses and human motor control during locomotion

CURRENT OPINION IN BIOMEDICAL ENGINEERING, 20.

By: H. Huang n , J. Si*, A. Brandt n & M. Li n

Contributors: H. Huang n , J. Si*, A. Brandt n & M. Li n

author keywords: Robotic lower limb prostheses; Human-prosthesis symbiosis; Human- in-the-loop optimization; Reinforcement learning; Gait biomechanics; Augmented biofeedback
TL;DR: This work advocates for new holistic approaches in which human motor control and intelligent prosthesis control function as one system (defined as human-prosthesis symbiosis), thereby improving the functionality and acceptance of robotic prostheses and users' quality of life. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: September 20, 2021

2021 article

Toward Expedited Impedance Tuning of a Robotic Prosthesis for Personalized Gait Assistance by Reinforcement Learning Control

Li, M., Wen, Y., Gao, X., Si, J., & Huang, H. (2021, May 26). IEEE TRANSACTIONS ON ROBOTICS, Vol. 5.

By: M. Li n, Y. Wen n, X. Gao *, J. Si* & H. Huang n 

Contributors: M. Li n, Y. Wen n, X. Gao *, J. Si* & H. Huang n 

author keywords: Tuning; Impedance; Knee; Prosthetics; Legged locomotion; Robustness; Kinematics; Impedance control; knee prosthesis; policy iteration; rehabilitation robotics; reinforcement learning (RL)
TL;DR: A policy iteration with constraint embedded (PICE) method as an innovative solution to the problem under the framework of reinforcement learning, using a projected Bellman equation with a constraint of assuring positive semidefiniteness of performance values during policy evaluation. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: October 18, 2021

2021 article

User Controlled Interface for Tuning Robotic Knee Prosthesis

2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), pp. 6190–6195.

By: A. Alili n, V. Nalam n, M. Li n, M. Liu n, J. Si* & H. Huang n 

Contributors: A. Alili n, V. Nalam n, M. Li n, M. Liu n, J. Si* & H. Huang n 

TL;DR: An intuitive interface designed for the prosthesis users and clinicians to choose the preferred knee joint profile during gait and use the autotuner to replicate in the prosthetics to address the challenges of manual tuning methods. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: January 7, 2022

2020 journal article

Wearer-Prosthesis Interaction for Symmetrical Gait: A Study Enabled by Reinforcement Learning Prosthesis Control

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 28(4), 904–913.

By: Y. Wen n, M. Li n, J. Si* & H. Huang n 

Contributors: Y. Wen n, M. Li n, J. Si* & H. Huang n 

author keywords: Prosthetics; Knee; Impedance; Legged locomotion; Robot kinematics; Tuning; Wearer-prosthesis interaction; robotic knee prosthesis; reinforcement learning; gait asymmetry; anteroposterior impulse
MeSH headings : Amputees; Artificial Limbs; Biomechanical Phenomena; Gait; Humans; Knee Joint; Prosthesis Design; Walking
TL;DR: The results suggest that it is possible to personalize transfemoral prosthesis control for improved temporal-spatial gait symmetry, and indicated that the RL-based prosthesis tuning system was a potential tool for studying wearer-prosthesis interactions. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: May 8, 2020

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