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SpikeNAS-Bench: Benchmarking NAS Algorithms for Spiking Neural Network Architecture
Genchen Sun;Zhengkun Liu;Lin Gan;Hang Su;Ting Li;Wenfeng Zhao;Biao Sun
IEEE Transactions on Artificial Intelligence
Year: 2025 | Early Access Article |
In recent years, Neural Architecture Search (NAS) has marked significant advancements, yet its efficacy is marred by the dependence on substantial computational resources. To mitigate this, the development of NAS benchmarks has emerged, offering datasets that enumerate all potential network architectures and their performances within a predefined search space. Nonetheless, these benchmarks predomi...Show More
Exploring the Potential of Fuzzy Sets in Cyborg Enhancement: A Comprehensive Review
IEEE Transactions on Fuzzy Systems
Cited by: Papers (1)
In an era marked by the rapid advancement of information technology, individuals now have the ability to enhance their organic bodies with mechanical and computational devices, revolutionizing their capabilities in everyday activities. However, the seamless integration of biosignals with mechanical counterparts continues to pose significant challenges. To address this, fuzzy logic (FL) emerges as ...Show More
Graph Representation Learning and Optimization for Spherical Emission Source Microscopy System
Xiaorui Liu;Zijie Li;Weihua Zong;Hang Su;Peng Liu;Shuzhi Sam Ge
Emission source microscopy (ESM) technique can be utilized for the localization of electromagnetic interference (EMI) sources in electronic systems, its performance greatly depends on the scanner accuracy and back-propagation method. In this paper, we introduce a novel spherical ESM system driven by 6-DOF manipulator, and investigate the back-propagation based on sphere wave expansion and robot co...Show More
Integrating Flexible Wearable Sensors and Embodied Intelligence: Reach the Unreachable
2024 IEEE Conference on Telepresence
Year: 2024 | Conference Paper |
In the field of robotic teleoperation, the integration of flexible wearable sensors with embodied intelligence has recently emerged as an innovative strategy. The adaptability and pliability of these sensors enable robots to accurately capture complex human motion data. By incorporating embodied intelligence, robots can actively engage with their environment, thus supplanting human decision-making...Show More
A Bioinspired Virtual Reality Toolkit for Robot-Assisted Medical Application: BioVRbot
Hang Su;Francesco Jamal Sheiban;Wen Qi;Salih Ertug Ovur;Samer Alfayad
The increasingly pervasive usage of robotic surgery not only calls for advances in clinical application but also implies high availability for preliminary medical education using virtual reality. Virtual reality is currently upgrading medical education by presenting complicated medical information in an immersive and interactive way. A system that allows multiple users to observe and operate via s...Show More
Mechanical Design of a Humanoid Robotic Head for Human Robot Interaction
Sevag Yahnian;Maya Sleiman;Naima Ait Oufroukh;Hang Su;Samer AlFayad
2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2024 | Conference Paper |
The emerging demand for robots that can interact naturally and effectively with humans in modern environments such as healthcare, service industries, and personal assistance highlights the need for developing expressive humanoid robotic heads. These heads should integrate advanced mechanical designs and control systems to achieve lifelike human interactions and movements. This paper details the de...Show More
An Efficient Human Activity Recognition Framework Based on Graph Convolutional Network for Human-Robot Collaboration
2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2024 | Conference Paper |
In this paper, a collaborative human-robot object processing framework based on skeleton data and graph convolutional human action recognition is proposed, and network architecture search and adaptive graph mechanisms are introduced. By recognizing the pose that the human carries the object, it is passed to the collaborative robot to make a matching object pickup action. The method is driven by th...Show More
HydROS 104: Interactive ROS compatible Electro-Hydraulic Educational Platform
Maya Sleiman;Maysoon Ghandour;Subhi Jleilaty;Mohamad Kardofaki;Hang Su;Samer AlFayad
2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2024 | Conference Paper |
Actuation is the cornerstone on which each mechatronics device is built. Hydraulic actuation offers features that no other actuators can provide. In particular, it provides high power-weight and high power-volume ratios that are indispensable for portable devices. At the hardware level, recent trends have led to the development of electro-hydraulic actuators. Those actuators combine the advantages...Show More
Mechatronic Development of Highly Integrated Electromagnetic Actuator (HIERA) for Scalable Adolescent Exoskeletons
Mohamad Kardofaki;Moustafa A. Fouz;Nahla Tabti;Hang Su;Eric Dychus;Samer Alfayad
2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2024 | Conference Paper |
Exoskeletons are widely used in robotic rehabilitation to improve the quality of life for disabled patients. However, existing exoskeletons lack scalability for teenagers due to their rapid growth. This study presents the Highly Integrated Electromagnetic Actuator (HIERA), a novel compact electric joint actuator designed to address this need. HIERA’s mechatronics development focuses on key design ...Show More
The Methodology of Quantitative Social Intention Evaluation and Robot Gaze Behavior Control in Multi-Objects Scenario
IEEE Transactions on Cognitive and Developmental Systems
Year: 2024 | Early Access Article |
This paper focuses on the multiple objects selection problem for the robot in social scenarios, and proposes a novel methodology composed of quantitative social intention evaluation and gaze behavior control. For the social scenarios containing various persons and multimodal social cues, a combination of the entropy weight method (EWM) and gray correlation-order preference by similarity to the ide...Show More
Human-Robot Collaboration Through a Multi-Scale Graph Convolution Neural Network With Temporal Attention
Collaborative robots sensing and understanding the movements and intentions of their human partners are crucial for realizing human-robot collaboration. Human skeleton sequences are widely recognized as a kind of data with great application potential in human action recognition. In this letter, a multi-scale skeleton-based human action recognition network is proposed, which leverages a spatio-temp...Show More
Sensor Fusion Based Humanoid Robotic arm Control*
Furong Chen;Feilong Wang;Xiaolong Yang;Qi Yong;Yanling Dong;Yi Gao;Long Zheng;Hang Su
2023 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2023 | Conference Paper |
This paper aims to study the teleoperation method based on multi-sensor fusion to achieve precise control of the robotic arm. The paper proposes a remote operation method based on multi-sensor fusion, which combines Kinect sensor, goniometer and data glove to realize the precise measurement and control of the upper limb joint angle. The adaptive Kalman filter algorithm is introduced to automatical...Show More
An Edge-Fog-Cloud-based Hierarchical Adaptive Model for Human-Robot Interaction*
2023 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
With the rapid advancement of intelligent devices and the Internet of Things (IoT), a vast amount of detailed information can now be captured and analyzed from the human body. This progress has led to the development of more comprehensive and versatile Body Area Networks (BANs). Despite this promising landscape, the field lacks mature global applications, and numerous challenges await resolution, ...Show More
Integrating Sensor Fusion for Teleoperation Control of Anthropomorphic Dual-Arm Robots*
Feilong Wang;Furong Chen;Xiaolong Yang;Qi Yong;Yanling Dong;Xinming Zhang;Long Zheng;Hang Su
2023 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
In order to achieve accurate control of anthropo-morphic two-arm robots, a novel teleoperation control system is proposed. The system uses sensor fusion technology to analyze and process the position and attitude information of the human arm, so as to realize the real-time control of the humanoid two-arm robot and its bionic hand. The system ensures stable and reliable remote operation, enabling u...Show More
Toward Safe Human-Robot Interaction: More Efficient Safety Monitoring Technology For Robotic Arms
2023 WRC Symposium on Advanced Robotics and Automation (WRC SARA)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Presently, advanced humanoid robotic arms have the ability to work independently, and although most current research can make the robotic arm react appropriately and autonomously to the changing environment, it cannot completely prevent the robotic arm from reacting incorrectly due to a variety of uncontrollable factors; therefore, it is necessary to detect the overall posture of the operating rob...Show More
A Control Strategy of Robot Eye-Head Coordinated Gaze Behavior Achieved for Minimized Neural Transmission Noise
Many studies have demonstrated the necessity to drive robot displaying natural and appropriate behaviors in social scenes. In this article, efforts were taken to restore the mechanism of human gaze behavior that can be highly informative for robot-human interaction. In order to determine the rules that biological plants obey in gaze behavior, we modeled the eye-head coordinated gaze behavior as a ...Show More
A 3D-CLDNN Based Multiple Data Fusion Framework for Finger Gesture Recognition in Human-Robot Interaction
2022 4th International Conference on Control and Robotics (ICCR)
Year: 2022 | Conference Paper |
Cited by: Papers (4)
Finger gesture recognition using surface electromyography (sEMG) became an efficient Human-Robot Interaction (HRI) solution. Although Machine Learning (ML) techniques are widely applied in this field, the general solutions for labeling and collecting big datasets impose time-consuming implementation and heavy workloads. In this paper, a new deep learning structure, namely three-dimensional convolu...Show More
Multimodal Emotion Recognition Based on Feature Fusion
2022 International Conference on Advanced Robotics and Mechatronics (ICARM)
Year: 2022 | Conference Paper |
In the field of human-computer interaction, human emotion recognition is a challenging problem, and it is also a key link to achieve barrier-free communication between human and machine. At present, most of the emotion recognition algorithms are constructed based on single modal social information, and the recognition results are one-sided and easily disturbed. The recognition accuracy is often di...Show More
Improved Kernel Correlation Filter Based Moving Target Tracking for Robot Grasping
Tracking and grasping moving objects are hot topics in the field of robots, which provides great potential in the industrial scene and human–computer cooperation. Based on the kernel correlation filter and vision 3-D reconstruction, this article proposes a visual-based tracking and grasping method for moving targets. An improved algorithm based on the kernel correlation filter is proposed for obje...Show More
Human-in-the-Loop Control of Soft Exosuits Using Impedance Learning on Different Terrains
IEEE Transactions on Robotics
Cited by: Papers (93)
Many previous works of soft wearable exoskeletons (exosuit) target at improving the human locomotion assistance, without considering the impedance adaption to interact with the unpredictable dynamics and external environment, preferably outside the laboratory environments. This article proposes a novel hierarchical human-in-the-loop paradigm that aims to produce suitable assistance powers for cabl...Show More
A Cybertwin Based Multimodal Network for ECG Patterns Monitoring Using Deep Learning
In next-generation network architecture, the Cybertwin drove the sixth generation of cellular networks sixth-generation (6G) to play an active role in many applications, such as healthcare and computer vision. Although the previous sixth-generation (5G) network provides the concept of edge cloud and core cloud, the internal communication mechanism has not been explained with a specific application...Show More
Fuzzy Approximation-Based Task-Space Control of Robot Manipulators With Remote Center of Motion Constraint
The presence of unknown physical interaction between the patients’ body and surgical tool in laparoscopic surgery requires a secure end-effector positioning while assuring a reliable constraint motion. In this work, a task-space control approach based on fuzzy approximation is proposed for a teleoperated surgery scenario utilizing a serial redundant robot manipulator (7 degrees of freedom), the mo...Show More
A Small Opening Workspace Control Strategy for Redundant Manipulator Based on RCM Method
This article presents a method for redundant manipulators working in the small opening workspace without collision. To achieve this aim, we began with an improved incremental radial basis function (RBF) neural network (RBFNN) method to estimate manipulator dynamic parameters, and then with the help of Lyapunov function, the control strategy could converge within a fixed time. To avoid the collisio...Show More
Asymmetric Cooperation Control of Dual-Arm Exoskeletons Using Human Collaborative Manipulation Models
IEEE Transactions on Cybernetics
Cited by: Papers (96)
The exoskeleton is mainly used by subjects who suffer muscle injury to enhance motor ability in the daily life environment. Previous research seldom considers extending human collaboration skills to human–robot collaborations. In this article, two models, that is: 1) the following the better model and 2) the interpersonal goal integration model, are designed to facilitate the human–human collabora...Show More
Adaptive Finite-Time Trajectory Tracking Control of Autonomous Vehicles That Experience Disturbances and Actuator Saturation
Hongbo Gao;Zhen Kan;Fei Chen;Zhengyuan Hao;Xi He;Hang Su;Keqiang Li
This article presents a finite-time tracking control scheme for autonomous vehicles. Trajectory tracking is difficult to control due to dynamic couplings and various disturbances and uncertainties. To cope with a lumped disturbance, a fuzzy logic system is designed. In particular, a novel adaptive algorithm is constructed to adjust the gain online, and it works well even without the prior informat...Show More
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