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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Hossein Kavianirad Francesco Missiroli Satoshi Endo Lorenzo Masia Sandra Hirche Chair of Information-oriented Control School of Computation Information and Technology Technical University of Munich Munich Germany Assistive Robotics and Interactive ExoSuits (ARIES) Lab Institute for Computer Engineering (ZITI) Heidelberg University Heidelberg Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Functional electrical stimulation (FES), a lightweight wearable technology leveraging active muscle recruitment, can assist functional movement for rehabilitation and various activities of daily living. However, the intricate and user-specific nature of the neuromuscular response to FES, such as the induction of muscular fatigue and discomfort, can lead to incomplete or imprecise functional movements. On the other hand, soft exoskeleton gloves, another form of lightweight wearable technology for hand movement assistance, guide movement externally with higher precision. In this research, therefore, we present a novel hybrid system that combines a soft exoskeleton glove and FES technology. Such an augmented hybrid system could reinforce the advantages of active muscle recruitment as a primary source of actuation with external actuation of the exoskeleton compensating for the limitations of FES in torque generation. Our objective is to investigate the performance of this hybrid system compared to the standalone FES system through experimental evaluation.

关键词： Torque Neuromuscular Exoskeletons Biomechatronics Fatigue Iron Hybrid power systems Neuromuscular stimulation Robots Recruitment

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Nonlinear Modes as a Tool for Comparing the Mathematical Structure of Dynamic Models of Soft Robots

arXiv

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arXiv 2024年

作者： Pustina, Pietro Calzolari, Davide Albu-Schäffer, Alin De Luca, Alessandro Della Santina, Cosimo Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Institute of Robotics and Mechatronics German Aerospace Center Oberpfaffenhofen82234 Germany Department of Informatics Technical University of Munich Garching85748 Germany Department of Cognitive Robotics Delft University of Technology Delft Netherlands

Continuum soft robots are nonlinear mechanical systems with theoretically infinite degrees of freedom (DoFs) that exhibit complex behaviors. Achieving motor intelligence under dynamic conditions necessitates the development of control-oriented reduced-order models (ROMs), which employ as few DoFs as possible while still accurately capturing the core characteristics of the theoretically infinite-dimensional dynamics. However, there is no quantitative way to measure if the ROM of a soft robot has succeeded in this task. In other fields, like structural dynamics or flexible link robotics, linear normal modes are routinely used to this end. Yet, this theory is not applicable to soft robots due to their nonlinearities. In this work, we propose to use the recent nonlinear extension in modal theory –called eigenmanifolds– as a means to evaluate control-oriented models for soft robots and compare them. To achieve this, we propose three similarity metrics relying on the projection of the nonlinear modes of the system into a task space of interest. We use this approach to compare quantitatively, for the first time, ROMs of increasing order generated under the piecewise constant curvature (PCC) hypothesis with a high-dimensional finite element (FE)-like model of a soft arm. Results show that by increasing the order of the discretization, the eigenmanifolds of the PCC model converge to those of the FE model. © 2024, CC BY.

关键词： Structural dynamics

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Data Alignment Design for Robotic Programming by Demonstration Based on IMU and Optical Tracker

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IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1页

作者： Song, Kai-Tai Li, Bing-Yi Ou, Szu-Chen National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Graduate Degree Program of Robotics Hsinchu300093 Taiwan

This study proposes a data alignment design for sensor fusion of an optical target (OT) and an inertial measurement unit (IMU) to track the trajectory of a handheld tool for robot programming by demonstration (PbD). A novel method is proposed for coordinate and temporal alignment between the OT and the IMU sensor to increase tracking accuracy. The IMU measurements are aligned with the corresponding angular velocities and accelerations derived from the OT to calibrate the IMU-OT relationship. Global and local optimizations are combined to reduce the computation time for the temporal alignment and coordinate calibration. Experimental results show that the proposed method provides improved calibration results with shorter calculation time compared with the two existing methods. The sensor fusion experiments verify the accuracy of trajectory tracking of 1.3 mm using the calibration result, an improvement from 1.4 mm of the data alignment using ruler measurement. Integrated PbD experiments using a 6-DOF manipulator were carried out to evaluate the proposed method. The manipulator imitated the hand motion of a bottle transfer task with a trajectory error of 0.66 mm. Practical robotic experiments demonstrate that the method is suitable for robot programming applications. © 1963-2012 IEEE.

关键词： Calibration

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Multi-Agent Distributed DQN and Transfer Learning for Energy-Efficient Power Management in Solar Energy-Harvested Small-Cell Networks

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IEEE Internet of Things Journal 2025年第12期12卷 19590-19604页

作者： Cho, Hyebin Kim, Hyungsub Na, JeeHyeon Lim, Seung-Chan Lee, Howon Hankyong National University School of Electrical Electronic and Control Engineering Anseong17579 Korea Republic of Electronics and Telecommunications Research Institute Daejeon34141 Korea Republic of Hankyong National University School of ICT Robotics and Mechanical Engineering and IITC Anseong17579 Korea Republic of Ajou University Department of Electrical and Computer Engineering Suwon16499 Korea Republic of

The integration of solar energy harvesting into small-cell networks is a promising solution for achieving energy-efficient and sustainable wireless communications. However, the inherent variability and intermittency of solar energy, coupled with precise inter-cell interference management, significantly hinder efficient network operation. To resolve these challenges, we propose a multi-agent distributed deep Q-network (MA-DDQN) framework, where the distributed base stations learn the optimal transmit power control policies. To further enhance adaptability under varying solar conditions, we present a daily model transfer with a fine-tuning approach, enabling efficient deployment without extensive training overhead. Simulation results demonstrate that the proposed methods remarkably improve energy efficiency while maintaining robust adaptability under dynamic solar conditions, revealing their potential for sustainable small-cell network deployments. © 2014 IEEE.

关键词： Solar cell efficiency

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COG: COnsistent Data AuGmentation for Object Perception 15th

COG: COnsistent Data AuGmentation for Object Perception

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15th Asian Conference on computer Vision, ACCV 2020

作者： He, Zewen Wu, Rui Zhang, Dingqian Institute of Automation Chinese Academy of Sciences Beijing China School of Computer and Control Engineering University of Chinese Academy of Science Beijing China Horizon Robotics Beijing China

ISBN: (纸本)9783030695347

Recently, data augmentation techniques for training conv-nets emerge one after another, especially focusing on image classification. They’re always applied to object detection without further careful design. In this paper we propose COG, a general domain migration scheme for augmentation. Specifically, based on a particular augmentation, we first analyze its inherent inconsistency, and then adopt an adaptive strategy to rectify ground-truths of the augmented input images. Next, deep detection networks are trained on the rectified data to achieve better performance. Our extensive experiments show that our method COG’s performance is superior to its competitor on detection and instance segmentation tasks. In addition, the results manifest the robustness of COG when faced with hyper-parameter variations, etc. © 2021, Springer Nature Switzerland AG.

关键词： Object detection

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Enhancement of Two-Photon Fluorescence Microscopy Through Auxiliary Microspheres for Microscopic Observation

Enhancement of Two-Photon Fluorescence Microscopy Through Au...

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IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Feng Zhang Zijian Jin Chaodi Jiang Shuai Yuan Yongliang Yang Xiaoduo Wang School of Electrical & Control Engineering Shenyang Jianzhu University Shenyang Liaoning Province China School of Computer Science and Engineering Shenyang Jianzhu University Shenyang Liaoning Province China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

At present, it is still a great challenge to improve the observation accuracy of two-photon fluorescence microscope. A new method that using auxiliary microspheres as movable components on the sample is proposed to solve this challenge in this study, it can improve high-resolution imaging. In experiments using two-photon fluorescence microscopy, the half-width height (FWHM) of red fluorescent nanoparticles with a diameter of 20 nm was observed to be 296 nm using a primitive microscope system. In this paper by combining barium titanate microspheres with two-photon fluorescence microscopy, the accuracy of the point spread function of the nanoparticles can be improved by a factor of about 1.65, which results in a significant reduction of their half-width height measurements to 179 nm. The research is of great significance to improve the resolution of two-photon fluorescence microscope. This progress is very valuable for studying biological tissues and cell structures, it provides a new impetus for the sustainable development in the microscopic imaging field.

关键词： Nanoparticles Accuracy Barium Microscopy Refractive index High-resolution imaging Fluorescence Titanium compounds Sustainable development Intelligent systems

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Protein-Folding Inspired Programmable control System for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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IEEE International Conference on robotics and Biomimetics

作者： Feng Zhang Yuping Gu Zebin Wang Shuai Yuan Yongliang Yang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Liaoning China School of Computer Science and Engineering Shenyang Jianzhu University Shenyang Liaoning China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem.

关键词： Proteins Vibrations Programmable control Animals Morphology Swarm robotics Programming control systems Robustness Robots

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Trajectory Learning and Demonstration of a Robot Manipulator Based-on Sensor Fusion from a Hand-held Tool

Trajectory Learning and Demonstration of a Robot Manipulator...

引用

International Automatic control Conference

作者： Kai-Tai Song Szu-Chen Ou Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Yang Ming Chiao Tung University Hsinchu Taiwan ROC Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan ROC

ISBN: (数字)9798350354904

ISBN: (纸本)9798350354911

This paper presents a programming system for a robot manipulator using a hand-held demonstration tool. In this system, a user holds the self-designed tool to demonstrate a desired motion path, and the robot arm replicates the learned trajectory. The path-demonstration tool, including optical tags (OT) and an IMU, is designed to collect trajectory data from hand motion. Sensor data fusion allows the system to track accurately the demonstrated trajectory. A calibration procedure is proposed to transform the trajectory from tool’s coordinate system to robot’s coordinate system. A cubic spline-based trajectory planning method is proposed to ensure smooth reproduction of the learned trajectory in both time and space. Experimental results show that the robot is able to replicate squared and curved trajectories collected from the path-demonstration tool. The average position error is within 2.435 mm in XYZ directions and the average orientation error is within 0.65 degrees.

关键词： Trajectory planning Tracking Robot kinematics Transforms Sensor fusion Programming Robot sensing systems Manipulators Trajectory Splines (mathematics)

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A Design for Improvement of Visual SLAM in Dynamic Environments Using Feature-Point Removal of Moving Persons

A Design for Improvement of Visual SLAM in Dynamic Environme...

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International Automatic control Conference

作者： Kai-Tai Song Ching-Hao Meng Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of Robotics College of Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

This paper presents a design to improve the robustness of visual SLAM(vSLAM). A processing step of feature-removal is added to the tracking thread of the conventional ORB-SLAM2 algorithm to improve the localization accuracy of a mobile robot in an environment with moving persons. Instance segmentation and motion tracking are intergrated to identify motion state of people in an image. ORB feature points belonging to moving persons are removed for further processing of the vSLAM pipeline. The advantage of this method is that the vSLAM can remove feature points of moving people, while retain those belonging to static people in the environment, which improves the accuracy of robot pose estimation. The improved ORB-SLAM2 algorithm has been implemented in a NVIDIA Xavier embedded system, which is integrated to a mobile robot. In practical robot navigation experiments, the average positioning error of the proposed method is within 4cm for 22.4m travel distance. Compared with conventional ORB-SLAM2, the average accuracy of our vSLAM method improves 97% in a dynamic environment with moving people.

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RoboFold: A platform for Protein-folding Inspired Robot Swarms *

RoboFold: A platform for Protein-folding Inspired Robot Swar...

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WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Feng Zhang Yuping Gu Shuai Yuan Yongliang Yang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang Liaoning China School of Computer Science and Engineering and School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China

Natural swarms have inspired various controlling algorithms for swarm robotics, while few of them were programmed in a similar way as the natural swarms. Defining a reliable programming method is still a daunting challenge in swarm robotics. In nature, the information of 3D protein structure is programmed in the sequence of amino acids of the protein. To mimic the programming method of protein folding, we present a platform for investigating protein-folding inspired programming method for robot swarms. This platform includes three parts: a vibration machine, protein-like robot sequences, and recording devices. The preliminary results presented here demonstrated the effectiveness of this platform and the feasibility of protein-folding inspired programming method for robot swarms.

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