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作者： Ueda, Jun Matsugashita, Masayuki Oya, Reishi Ogasawara, Tsukasa Robotics Laboratory Graduate School of Information Science Nara Institute of Science and Technology Nara 630-0192 Japan d'Arbeloff Laboratory for Information Systems and Technology Mechanical Engineering Massachusetts Institute of Technology Cambridge MA 02139 United States

ISBN: (纸本)9783540774563

The aim of this paper is to arbitrarily modify the load force of any selected muscle by using an exoskeleton, thus enabling "pinpointed" motion support, rehabilitation, and training. An advanced dynamic model, called a musculoskeletal-exoskeletal integrated human model, is developed. The driving-forces of the pneumatic actuators are designated by a muscle force control algorithm using the integrated model. A prototype power-assisting system has been developed using pneumatic rubber actuators. The validity of the method has been confirmed by measuring surface electromyographic (EMG) signals of related muscles. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Musculoskeletal system

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Cooperative range-based navigation using a beacon with circular motion installed on board the support platform

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IFAC-PapersOnLine 2019年第21期52卷 390-395页

作者： Santiago Rúa Naveen Crasta Rafael E. Vásquez Manuel J. Betancur Antonio M. Pascoal Universidad Pontificia Bolivariana Circular 1 # 70-01 School of Engineering 050031 Medellín Colombia Laboratory of Robotics and Systems in Engineering and Science (LARSyS) IST/University of Lisbon Av. Rovisco Pais 1 1049-001 Lisbon Portugal

This work addresses the observability analysis for a cooperative range-based navigation system that uses a beacon with circular motion installed on board the support platform to find the location of an underwater vehicle. A nonlinear model is first obtained in order to describe the motion of the vehicle and the beacon, that is attached to the tip of a 1 DoF rotating arm (deployed from a stationary support platform or vessel). A state-space realization is obtained and augmented in order to convert the nonlinear system into a Linear Time Varying (LTV) system. Then, the observability analysis is performed for the new system considering its equivalence since the state trajectories of the LTV system have one-to-one correspondence to the state trajectories of the nonlinear system. We show that, when the vehicle moves in circles or in straight lines, it is possible to ensure observability by rotating the arm that has the beacon attached. This result is important from a theoretical point of view, and represents a new way of implementing range-based navigation systems, without relying on deviation of the vehicle’s mission or the need of another vehicle to ensure observability.

关键词： Vehicle guidance navigation Underwater vehicles Control system design applications Cooperative control Acoustic-Based Networked Control Navigation

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Robust Tracking for Electromagnetic-Actuated Microrobot Via Sliding Mode Control 49

Robust Tracking for Electromagnetic-Actuated Microrobot Via ...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Wu, Yihang Qu, Ziyao Chang, Xiaocong Hu, Zhijian Yang, Rongni Ma, Renjie Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Control Science and Engineering Shandong University Jinan China

ISBN: (纸本)9798350331820

Microrobots can work in small, enclosed spaces and complete complex tasks. It has potential applications in the field of biomedical and life sciences. This paper focuses on investigating robust dynamic tracking for electromagnetic-actuated microrobot via sliding mode control. First, we generalize the planar motion to the case of spatial trajectory tracking and then establish the three-dimensional tracking error model of microrobot. Then, we deploy a novel sliding control strategy and ensure the stability of sliding mode dynamics, once the robotic state reaches the sliding surface and sustains there in the sequel. Finally, the numerical simulation is conducted, compared to the traditional proportion-integration-differentiation control strategy, to verify the effectiveness and advantages of our proposed control scheme. © 2023 IEEE.

关键词： Sliding mode control

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A new active rehabilitation training mode for upper limbs based on Tai Chi Pushing Hands

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Biomimetic Intelligence & robotics 2024年第3期4卷 82-92页

作者： Xiangpan Li Liaoyuan Li Jianhai Han Bingjing Guo Ganqin Du School of Mechatronics Engineering Henan University of Science and TechnologyLuoyang 471003China Henan Provincial Key Laboratory of Robotics and Intelligent Systems Luoyang 471003China School of Automotive Engineering Hubei University of Automotive TechnologyShiyan 442002China Hubei Key Laboratory of Automotive Power Train and Electronic Control Shiyan 442002China The First Affiliated Hospital of Henan University of Science and Technology Luoyang 471003China

Robot-assisted rehabilitation is a crucial approach to restoring motor function in the ***,the current training trajectory lacks sufficient theoretical or practical support,and the monotony of single-mode training is a *** Chi Pushing Hands,a beneficial and effective daily exercise,has been shown to improve balance function,psychological state,and motor function of the upper extremities in patients recovering from *** address these issues,we propose a new active rehabilitation training that incorporates Tai Chi Pushing Hands movements and yin-yang balance *** training trajectory and direction are encoded by the velocity field and consist of two processes:yang(push)and yin(return).During yang,the limb actively pushes the robot to move,while during yin,the limb actively follows the robot’s *** provide necessary assistance,an admittance controller with self-adaptive parameters is *** addition,we introduce two indexes,the‘Intention Angle’(ϖ)and the time ratio(Γ),to evaluate motion perception *** experiment was conducted on a 4-degree-of-freedom upper limb rehabilitation robot platform,and the subjects were separated into a familiar group and an unfamiliar *** experiment results show that the training could be completed well no matter whether the subject is familiar with Tai Chi Pushing Hands or *** parameters and the movement of the robot can be adjusted based on the interactive force to adapt to the ability of the subject.

关键词： Tai Chi Push Hands Velocity field Self-adaptive admittance Upper limb rehabilitation Active training

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Heuristics-based Adaptive Biased Random Walk Algorithm for Chemical Source Localization using AUVs

Heuristics-based Adaptive Biased Random Walk Algorithm for C...

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OCEANS

作者： Shubham Garg Antonio Pascoal Sanjeev Afzulpurkar Laboratory of Robotics and Engineering Systems (LARSyS) ISR/IST University of Lisbon Portugal Marine Instrumentation Division National Institute of Oceanography Goa India

We draw inspiration from the behavior of single-celled organisms to present a chemotaxis-inspired Adaptive Biased Random Walk (ABRW) guidance-control law for an Autonomous Underwater Vehicle (AUV). We build on previous results available in the literature to derive a random-walk based guidance-control law for an AUV to track-in and localize a potential chemical source in a turbulence-dominated environment. The ABRW-Strategy makes use of common plume-tracking and heuristic schemes for real-time path planning of the AUV. We further draw out a more comprehensive study of the guidance-strategy and extend the work for implementation in the Medusa class of vehicles that are developed in-house by Instituto Superior Tecnico (IST). The performance of the system is assessed via Hardware-in-the-loop (HIL) simulations to illustrate the viability of using random-walk for chemical source localization. The results obtained are encouraging for in-water tests with an autonomous vehicle of the Medusa class aiming at the validation of the proposed guidance-strategy in real-time experiments.

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Saturated Output Feedback Control of a Quadrotor Aircraft

Saturated Output Feedback Control of a Quadrotor Aircraft

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American Control Conference

作者： D. Cabecinhas R. Cunha C. Silvestre Department of Electrical Engineering and Computer Science and Institute for Robotics and Systems in Engineering and Science (LARSyS) Instituto Superior Tecnico Universidade Tecnica de Lisboa 1049-001 Lisboa Portugal

ISBN: (数字)9781457710964

ISBN: (纸本)9781457710957

This paper addresses the problem of steering a quadrotor vehicle along a prescribed trajectory. The problem is formulated so as to enforce bounds on the thrust actuation and present robustness against possible disturbances resulting from errors in the estimation of the aircraft state. The proposed solution consists of a nonlinear state feedback controller for thrust and torque actuation that i) guarantees asymptotic stability of the closed-loop system in the presence of exponentially decaying observer errors, ii) ensures global regulation of the trajectory tracking errors, and iii) defines the thrust actuation as a saturated function of the position and linear velocity errors. Simulation results are presented to assess the performance and robustness of the proposed controller.

关键词： Trajectory Vehicles Observers Lyapunov methods Convergence Vectors Robustness

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All-weather,natural silent speech recognition via machine-learning-assisted tattoo-like electronics

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npj Flexible Electronics 2021年第1期5卷 183-191页

作者： Youhua Wang Tianyi Tang Yin Xu Yunzhao Bai Lang Yin Guang Li Hongmiao Zhang Huicong Liu YongAn Huang State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhanChina Flexible Electronics Research Center Huazhong University of Science and TechnologyWuhanChina School of Mechanical and Electric Engineering Jiangsu Provincial Key Laboratory of Advanced RoboticsSoochow UniversitySuzhouChina State Key Laboratory of Industrial Control Technologyg Institute of Cyber Systems and ControlZhejiang UniversityHangzhouChina

The internal availability of silent speech serves as a translator for people with aphasia and keeps human–machine/human interactions working under various *** paper develops a silent speech strategy to achieve all-weather,natural *** strategy requires few usage specialized skills like sign language but accurately transfers high-capacity information in complicated and changeable daily *** the strategy,the tattoo-like electronics imperceptibly attached on facial skin record high-quality bio-data of various silent speech,and the machine-learning algorithm deployed on the cloud recognizes accurately the silent speech and reduces the weight of the wireless acquisition module.A series of experiments show that the silent speech recognition system(SSRS)can enduringly comply with large deformation(~45%)of faces by virtue of the electricitypreferred tattoo-like electrodes and recognize up to 110 words covering daily vocabularies with a high average accuracy of 92.64%simply by use of small-sample machine *** successfully apply the SSRS to 1-day routine life,including daily greeting,running,dining,manipulating industrial robots in deafening noise,and expressing in darkness,which shows great promotion in real-world applications.

关键词： translator weather silent

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Optimal Sensor Trajectories for Mobile Underwater Target Positioning with Noisy Range Measurements

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IFAC Proceedings Volumes 2014年第3期47卷 5139-5144页

作者： D. Moreno-Salinas A.M. Pascoal J. Aranda Department of Computer Science and Automatic Control National University Distance Education (UNED) Spain Laboratory of Robotics and Systems in Engineering and Science (LARSyS) Instituto Superior Tecnico (IST) University of Lisbon Portugal Adjunct Scientist National Institute of Oceanography (NIO) Goa India

There is considerable interest in reducing the number of sensors/beacons involved in underwater positioning/navigation systems since this has the potential to drastically reduce the costs and the time spent in deploying, calibrating, and recovering acoustic equipment at sea. Motivated by these considerations, we address the problem of single underwater target positioning based on acoustic range measurements between the target and a moving sensor at the sea surface. In particular, the goal of the present work is to compute optimal geometric trajectories for the surface sensor that will, in a well defined sense, maximize the range-related information available for underwater target positioning and tracking. To this effect, the Fisher Information Matrix and the maximization of its determinant are used to determine the sensor trajectory that yields the most accurate positioning of the target, while the latter describes a preplanned trajectory. It is shown that the optimal trajectory depends on the velocity of the sensor, the velocity and trajectory of the target, the sampling time between measurements, the measurement error model, and the number of measurements used to compute the FIM. Simulation examples illustrate the key results derived.

关键词： Autonomous underwater vehicles Fisher information matrix Cramer-Rao Bound optimization positioning single tracker

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Predict Hip Joint Moment Using CNN for Hip Exoskeleton Control 1

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Zhang, Yuanwen Xiong, Jingfeng Qian, Yuepeng Chen, Xinxing Guo, Yixuan Fu, Chenglong Leng, Yuquan Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China National University of Singapore Singapore117583 Singapore

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

The assistance of the hip exoskeleton is closely related to hip joint moment, and the corresponding assistance can be generated by hip joint moment directly. However, it is difficult to obtain the hip joint moment directly from the sensor during walking. An effective method is to use deep learning models to predict hip joint moment using hip joint angle information. But there are still many challenges in applying this method to practical control systems. This study designs specific parameters to train a deep neural network for predicting hip joint moments and discusses the effects of the number of convolutional layers (N) and the length of sampling time (SL) on the prediction accuracy and the computation time in a real control system. Experiments show that for N ≤ 5, using angle information with SL ≤ 1.0 s achieves the highest prediction accuracy. However, for larger values of N (N > 5), the optimal SL becomes to be longer, where it increases to 2.0 s and the corresponding RMSE is 0.06260 Nm/kg and 0.05977 Nm/kg, respectively. These results indicate the importance of SL for prediction accuracy. Furthermore, a comparative analysis of the computation time with models using different N and SL is performed, and the relationship between computation time and prediction accuracy is discussed. This study provides specific model training parameters and detailed comparative analysis, which facilitates further application of deep learning models on hip exoskeletons. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Forecasting

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A Survey of Deep Learning-based Hand Pose Estimation 8

A Survey of Deep Learning-based Hand Pose Estimation

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8th IEEE International Conference on Cloud Computing and Intelligence systems, CCIS 2022

作者： Wang, Shuaibing Wang, Shunli Kuang, HaoPeng Li, Fang Qian, Ziyun Li, Mingcheng Zhang, Lihua Fudan University Academy for Engineering & Technology China Ministry of Education Engineering Research Center of Ai and Robotics China Jilin Provincial Key Laboratory of Intelligence Science & Engineering China Ai & Unmanned Systems Engineering Research Center of Jilin Province China

ISBN: (纸本)9781665477352

Hand pose estimation is one of the representative tasks in computer vision. Solving the hand pose estimation problem is essential for various fields such as virtual reality, augmented reality, mixed reality, and human-computer interaction. Due to the significant development of deep learning techniques, the hand pose estimation task has reached significant performance on many hand pose estimation datasets. However, the hand pose estimation task still faces many challenges due to the lack of large-scale labeled data, severe occlusion, low hand resolution, and background clutter. To better understand the hand pose estimation task, this paper presents a comprehensive survey of outstanding papers over the last five years. The paper first introduces 19 common hand pose estimation datasets, then extensively discusses some of the mainstream approaches in hand pose estimation, including fully supervised, semi-supervised, weakly supervised, and self-supervised learning methods. Finally, we extensively discuss the future evolution trends of hand pose estimation. © 2022 IEEE.

关键词： Computer vision

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