Author name cluster

Yili Fu

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8 papers

2 author rows

IROS Conference 2025 Conference Paper

sEMG-Based Continues Motion Prediction of Shoulder exoskeleton Control Using the VGANet Model

Tongxin Jiang
Fuhai Zhang
Lei Yang
Tianyang Wu
Yili Fu

Wearable exoskeleton robots play a crucial role in promoting upper limb function recovery. To enhance human-robot interaction and achieve precise control, continuous prediction of limb joint angles is required. This paper proposes a decoupled network model (VGANet) based on Variable Graph Convolutional Networks (V-GCN) and Temporal External Attention (TEA) for motion prediction in upper limb rehabilitation training. By establishing a mapping relationship between surface electromyography (sEMG) signals and upper limb movements, the model can predict future joint angles based on real-time sEMG signals. Experimental results demonstrate that this method can achieve continuous motion prediction for the shoulder joint and has been successfully applied to the control system of exoskeleton robots, providing an effective solution for the intelligent development of rehabilitation exoskeletons.

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IROS Conference 2025 Conference Paper

ULRVT II: A Novel Upper Limb Rehabilitation Robot with Joint Synergy Control and Evaluation for Virtual Training *

Lei Yang
Fuhai Zhang
Tianyang Wu
Tongxin Jiang
Yili Fu

Global population aging has led to a sharp increase in patients of upper limb motor dysfunction. Robot assisted virtual training, as a novel solution, can offer safe and precise assistance for upper limb rehabilitation. However, it remains a critical challenge to compensate virtual interaction force and realize joint synergy movement. In this paper, we design an upper limb rehabilitation robot for virtual training (ULRVT II) which is a cable driven exoskeleton with high compatibility controlled by a joint synergy method. Moreover, we establish a rehabilitation platform with a virtual training environment and evaluation system for experimental validation. Tests for the performance of joint synergy and virtual training are carried out to show the effectiveness of our robot.

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JBHI Journal 2022 Journal Article

sEMG-Based Gesture Recognition Using Deep Learning From Noisy Labels

Akram Fatayer
Wenpeng Gao
Yili Fu

Gesture recognition for myoelectric prosthesis control utilizing sparse multichannel surface Electromyography (sEMG) is a challenging task, and from a Muscle-Computer Interface (MCI) standpoint, the performance is still far from optimal. However, the design of a well-performed sEMG recognition system depends on the flexibility of the input-output function and the dataset’s quality. To improve the performance of MCI, we proposed a novel gesture recognition framework that (i) Enrich the spectral information of the sparse sEMG signals by constructing a fused map image (denoted as sEMG-Map) that integrates a multiresolution decomposition (by means of orthogonal wavelets) through the raw signals then rely upon the Convolutional Neural Network (CNN) capacity to exploit the composite hierarchies in the constructed sEMG-Map input. (ii) Deals with the label noise by proposing a data-centric method (denoted as ALR-CNN) that synchronously refines the falsely labeled samples and optimizes the CNN model based on two basic assumptions. First, the deep model accuracy improves as the training progress. Second, a set of successive learnable max-activated outputs of a well-performed deep model is a reliable estimator for motion detection in the muscle activation pattern. Our proposed framework is evaluated on three large-scale public databases. The average classification accuracy is 95. 50%, 95. 85%, and 85. 58% for NinaPro DB2, NinaPro DB7, and NinaPro DB3, respectively. The experimental results verify the effectuality of the proposed method and show high accuracy.

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ICRA Conference 2021 Conference Paper

Kinematic analysis of a flexible surgical instrument for robot-assisted minimally invasive surgery

Mei Feng
Zhixue Ni
Yili Fu
Xingze Jin
Wei Liu
Xiuquan Lu

Flexible surgical instruments can flexibly adjust their posture with a high degree of freedom, which makes them highly suitable for performing surgical tasks in narrow workspaces. However, redundant degrees of freedom increase their kinematic difficulty, which may cause redundant solutions, complex calculations, and low speeds. In this paper, a flexible surgical instrument is presented. The structural characteristics of this flexible instrument were explored in terms of force balance, it was concluded that the instrument had a constant curvature during bending. Based on this, the kinematics and inverse kinematics were solved via the geometric and Newton iteration methods, respectively. Our experiments showed that the proposed method for solving flexible instrument kinematics had high precision, a unique solution, and high speed; the instrument can be well controlled to perform refined operations. The proposed geometric method for solving the flexible instrument kinematics avoided the calculation of the Jacobian matrix, making it fast and capable of meeting the master-slave control requirement for real-time surgery. Furthermore, the proposed kinematics solution method is not limited by the mechanical structure, so it can be used for flexible instruments owning to its constant curvature bending.

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IROS Conference 2015 Conference Paper

A human-robot interaction modeling approach for hand rehabilitation exoskeleton using biomechanical technique

Fuhai Zhang
Xiangyu Wang
Yili Fu
Sunil K. Agrawal

Aiming at the physical coupling feature between the finger and the hand exoskeleton, a human-robot interaction modeling approach is proposed. The muscle motion formulas are established based on the finger physiological structure and Hill model. The equilibrium equations between exoskeleton and finger are connected by static analysis. In order to solve the redundancy problem of the system, a method based on the physiological cross-sectional area (PCSA) is adopted to get the optimized solution of muscle force, and an optimization method based on the total minimum error (TME) is presented to obtain the parameters of Hill model. The experimental setup is established to receive the finger data of motion and force for optimization. The approach proposed can get the quantifiable muscle parameters to study the statistical analysis of muscle motion and rehabilitation state. And it will be possible for the exoskeleton and the finger to be combined as a controlled plant so as to introduce muscle parameters into the controller design.

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IROS Conference 2006 Conference Paper

Avoiding Static and Dynamic Objects in Navigation

Han Li
Yili Fu
He Xu
Yulin Ma

Real-time collision free path planning involves avoidance of static as well as dynamic objects in unknown environment. Strategies suitable for stationary navigation cannot be suitable for the dynamic environment. Behavior-based control combined with fuzzy control to avoid dynamic and static obstacle is described in this paper. Behavior-based control helps the robot get over complex static environment or avoid dynamic objects according to different collision situation. Double-layered fuzzy logic control helps figure out velocity and steering angle of the robot based on some uncertain information. The method has been tested effectively through simulation by a mobile robot navigating amidst multiple static and dynamic environments

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ICRA Conference 2005 Conference Paper

Topological Analysis and Control on Mobile Robot with Partially-Failed Propulsive Wheel

Yili Fu
Xu He
Shuoguo Wang
Li Han
Yulin Ma

The issue how to make a mobile robot with some partially-failed propulsive wheels continuously navigate to its goal is rarely discussed. Based on a mobile robot with four individual propulsive wheels accompanied by corresponding independent steering devices, a novel control strategy with topological transformation on locomotion actuation is investigated to produce a desired motion. Some prototypes with different distribution of partially-failed propulsive wheels are analyzed. A new criterion for the motor selection is given to assure the trafficability in case of partial failure for propulsive wheels. Results from tests are presented to demonstrate the feasibility of proposed scheme.

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ICRA Conference 1999 Conference Paper

The Path Planning of Mobile Manipulator with Genetic-Fuzzy Controller in Flexible Manufacturing Cell

Xiaowei Ma
Yili Fu
Yufei Yuan
Wang Wei
Yulin Ma
Hegao Cai

This paper presents a new intelligent path planning method for motions of the mobile manipulator in flexible manufacturing cell. It simulates the way of human actions to control the mobile manipulator according to a master-slave hierarchical control strategy. The method can find path using the genetic fuzzy controller (GFC) while in moving, and switch to the collision-free path planner based on the critical collision joint angle (CCJA) and DA* algorithms when in requirement of performing the tasks such as load or unload. In this paper, the GFC is developed to automatically generate the fuzzy if-then rules from samples. In addition, a new modeling approach for manipulator is presented. It is called the c-space modeling based on CCJA. Using this technique, the computation time and memory space are greatly reduced. Moreover, a modified DA* algorithm with dynamic step-changeable and goal-visible-test is also used to accelerate the search process. Simulation results of the mobile manipulator performing object transporting task show the method presented is feasible.

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