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42nd Chinese Control Conference, CCC 2023

作者： Omar, Zakarya Liu, Ke-Xian Ren, Chao Meng, Qing-Hao Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin300072 China Sana'a University Faculty of Engineering Sana'a Yemen

ISBN: (纸本)9789887581543

A Multi-Joint Autonomous Underwater Vehicle (MJ-AUV) is designed and equipped with multiple movable segments or joints that allow for greater maneuverability and flexibility in the water. These joints allow the MJ-AUV to change its shape, orientation, and direction of movement, so it can access tight spaces or navigate in complex underwater environments, making it useful for a variety of tasks in the deep sea, such as surveillance, exploration, and maintenance. However, the multiple joint structure of the MJ-AUV complicates the dynamics of the system. Furthermore, the joints' rotation causes misalignment of the cabins, causing deviations in the desired forces and torques. To address these issues, this study focuses on the 2-dimensional (2D) modeling as well as the trajectory tracking controller of the MJ-AUV. In this setting, the proposed controller utilizes a hierarchically structured robust nonlinear back-stepping and sliding-mode approach. Hence, this controller is simulated under various uncertainties and disturbances and the results show that it presents a global finite-time convergence to a bounded neighborhood of the origin for both position and velocity tracking errors, demonstrating its effectiveness and robustness. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Autonomous underwater vehicles

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EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-LSTM Hybrid Model

EMG Based Rehabilitation Gesture Recognition Using DAE-CNN-L...

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2024 International Convention on Rehabilitation engineering and Assistive Technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Cao, Wujing Guo, Xinqiang Zou, Yupeng Zhang, Shuo Luo, Mingxiang Kobsiriphat, Worawarit Wu, Xinyu Yin, Meng Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518005 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems China School of Mechanical Engineering China University of Petroleum China National Metal and Materials Technology Center Thailand

ISBN: (纸本)9798350355123

Stroke, as one of the leading causes of long-term disability globally, often results in motor impairments, particularly in the hands, significantly affecting patients' daily activities and causing profound psychological trauma. Rehabilitation gesture recognition, as one of the key means of active rehabilitation medicine, holds significant potential in stroke rehabilitation, providing real-time feedback on patient progress and enabling personalized interventions to meet individual needs. Traditional gesture recognition methods face numerous challenges when dealing with stroke patient data, such as noise, motion blur, and individual differences. To address these challenges, this paper proposes a novel approach for stroke patient gesture recognition using deep learning models. We adopt a strategy combining denoising autoencoder (DAE), convolutional neural network (CNN), and long short-term memory (LSTM) to enhance the accurate recognition of hand movements in stroke patients. Specifically, DAE is utilized for denoising EMG signals, extracting features, and reducing noise to improve the signal's noise resistance. CNN is employed for spatial feature extraction, while LSTM captures temporal dependencies in gesture sequences. By integrating these three deep learning models, our aim is to enhance the accuracy and robustness of rehabilitation gesture recognition. We validate the proposed method's effectiveness on an EMG dataset from seven subjects through experiments and compare it with traditional machine learning and individual CNN and LSTM algorithms. Experimental results demonstrate significant performance improvements of our hybrid model in rehabilitation gesture recognition tasks, indicating promising application prospects and practical significance. © 2024 IEEE.

关键词： Convolutional neural networks

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A WLS-Based Step-by-Step Identification Method for Industrial Robot Dynamics Parameters

A WLS-Based Step-by-Step Identification Method for Industria...

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International Conference on Control, Automation and robotics (ICCAR)

作者： Qianjiang Wang Mingxiu Kong Chuancheng Bian Hao Hong State Key Laboratory of Robotics and System School of Mechatronics Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798350373172

ISBN: (纸本)9798350373189

In order to improve the accuracy of robot dynamics parameter identification, this paper designs a step-by-step identification method based on weighted least squares. The robot dynamics model is first linearized to obtain the minimum parameter set. Subsequently, the friction model is built separately and experiments are designed to recognize the joint friction parameters first. Based on this, the excitation trajectory of finite term Fourier series is designed and optimized and data are collected. The joint moments obtained from the difference between the overall experimentally collected moments and the calculated friction moments are used to obtain the complete robot dynamics parameters based on weighted least squares identification. Comparison of the designed overall identification experiments shows that the total moment residuals of this method are reduced by 35.52% compared with the one-time identification method, which proves the effectiveness of this method.

关键词： Parameter estimation Accuracy Automation Service robots Friction Industrial robots Kinetic theory

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A Time-Optimal Trajectory Planning Algorithm for Six-Degree-of-Freedom Robots Based on NURBS Curves

A Time-Optimal Trajectory Planning Algorithm for Six-Degree-...

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International Conference on Control, Automation and robotics (ICCAR)

作者： Hao Hong Minxiu Kong Jiawang Wang Qianjiang Wang School of Mechatronics Engineering Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (数字)9798350373172

ISBN: (纸本)9798350373189

In this paper, we research and analyse the practical needs of robotic arm to complete the complex path planning of robotic arm and smooth transition of multi-attitude in the shortest time under the premise of satisfying the dynamics constraints, and put forward the time-optimal trajectory planning based on NURBS curves and multi-attitude interpolation algorithm based on quaternion with NURBS curves. Using the complex nature of quaternions, the quaternions are converted into three-dimensional space points for curve interpolation, and finally converted back to quaternions to achieve the second-order continuity of multi-gesture interpolation; a time-optimal trajectory planning algorithm based on NURBS curves is designed, which discretises the curves, and fits the NURBS curves using the discrete points. At the same time, the optimal rate solution under all the constraints is calculated point by point according to the discrete points on the motion path, and the optimal velocity curve satisfying the dynamics constraints is obtained, so as to achieve the time-optimal trajectory planning. Finally, the feasibility of the designed trajectory planning algorithm is verified in the simulation software and experimental platform, and it is proved that the algorithm can effectively improve the running speed by at least 30%.

关键词： Surface reconstruction Interpolation Trajectory planning Service robots Quaternions Heuristic algorithms Software algorithms

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MC-Tac: Modular Camera-Based Tactile Sensor for Robot Gripper 16th

MC-Tac: Modular Camera-Based Tactile Sensor for Robot Gripp...

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

作者： Ren, Jieji Zou, Jiang Gu, Guoying Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Mechanical Engineering State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789819964949

Camera-based tactile sensors provide a convenient and low-cost approach for robot tactile perception. However, existing sensors are customized and only suit limited robots, which retards tactile applications. In this work, we proposed a modular design for camera-based tactile sensor to facilitate their integration on various robot grippers and fingers. Specifically, we disassemble tactile sensors into sense module for sensing surface interaction, receptor module for arranging camera, illumination, and structure elements, and adapter module for connection with robot gripper. Experiments show the proposed sensors can adopt various robot grippers and achieve high tactile perception performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Cameras

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Design and Motion Analysis of an Underactuated Finger Based on the Coupled and Self-Adaptive Linkage Mechanism

Design and Motion Analysis of an Underactuated Finger Based ...

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IEEE International Conference of Intelligent Robotic and Control engineering (IRCE)

作者： Wenshuo Yue Wenrui Wang Baoping Ma Hao Yang Guohua Cui Qirong Tang School of Mechanical and Automotive Engineering (Shanghai University of Engineering and Science) Laboratory of Robotics and Multibody System Tongji University Shanghai China Laboratory of Robotics and Multibody System Tongji University Shanghai China

Underactuated prosthetic hands possess excellent adaptability, yet they often suffer from issues such as complex structure, limited anthropomorphism, and reduced stability. To address these concerns, this paper presents a novel finger with coupled-adaptive functionality, consisting of three joints and two degrees of freedom (DOFs). It exhibits notable anthropomorphism, heightened stability, strong adaptability, and a simplified structure. This finger utilizes a novel coupled-adaptive linkage mechanism, enabling coupled motion in free space and self-adaptive motion while grasping diverse objects. Additionally, a series of simulation analyses have provided evidence that the finger can effectively and stably perform coupled movements and adaptively grasp objects of different shapes and sizes.

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Design, Modeling and Control of a Dielectric Elastomer Actuated Micro-positioning Stage 16th

Design, Modeling and Control of a Dielectric Elastomer Ac...

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

作者： Yan, Peinan Gu, Guoying Zou, Jiang Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789819964918

In this paper, we propose one kind of a dielectric elastomer actuated micro-positioning stage (DEAMS) that can achieve both large stroke and high resolution. To this end, a customized multilayer dielectric elastomer actuator (DEA), made of silicone, is designed and fabricated, which can generate a linear movement. Then based on the DEA, a DEAMS is designed with a stroke of nearly 1 mm and resolution of 480 nm. Next, several dynamic tests are conducted to reveal its dynamic responses: i) the natural frequency of the DEAMS can reach 80 Hz;ii) its output displacement shows both slow-time creep and rate-dependent hysteresis because of the inherent viscoelasticity. Lastly, a direct inverse hysteresis compensation (DIHC) controller based on a phenomenological hysteresis model and a closed-loop controller are adopted to remove hysteresis and creep, respectively. Experimental results demonstrate that with our control method, the DEAMS can achieve high-precision tracking control, which may pave the way for its applications in the field of micro/nano manipulations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Silicones

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Vascular-confined multi-passage discoidal nanoconstructs for the low-dose docetaxel inhibition of triple-negative breast cancer growth

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Nano Research 2022年第1期15卷 482-491页

作者： Alessia Felici Daniele Di Mascolo Miguel Ferreira Simone Lauciello Luca Bono Andrea Armirotti Arunkumar Pitchaimani Anna Lisa Palange Paolo Decuzzi Laboratory of Nanotechnology for Precision Medicine Fondazione Istituto Italiano di TecnologiaGenoa 16163Italy Department of Informatics BioengineeringRobotics and System EngineeringUniversity of GenoaGenoa 16126Italy Nanochemistry Laboratory Fondazione Istituto Italiano di TecnologiaGenoa 16163Italy Analytical Chemistry Laboratory Fondazione Istituto Italiano di TecnologiaGenoa 16163Italy

Taxane efficacy in triple negative breast cancer(TNBC)is limited by insufficient tumor accumulation and severe off-target *** offer a unique opportunity to enhance the anti-cancer potency of this ***,1,000 nm×400 nm discoidal polymeric nanoconstructs(DPN)encapsulating docetaxel(DTXL)and the near infrared compound Iipid-Cy5 were *** were obtained by filling multiple times cylindrical wells in a poly(vinyl alcohol)template with a polymer mixture comprising poly(lactic-co-glycolic acid)(PLGA)and poly(ethylene glycol)diacrylate(PEG-DA)chains together with therapeutic and imaging *** resulting“multi-passage”DPN exhibited higher DTXL loading,Iipid-Cy5 stability,and stiffness as compared to the conventional"single-passage"*** microscopy confirmed that DTXL-DPN were not taken up by MDA-MB-231 cells but would rather sit next to the cell membrane and slowly release DTXL *** DPN had no toxicity on TNBC cells,whereas DTXL-DPN presented a cytotoxic potential comparable to free DTXL(IC_(50)=2.6 nM±1.0 nM vs.7.0 nM±1.09 nM at 72 h).In orthotopic murine models,DPN accumulated in TNBC more efficiently than *** only 2 mg/kg DTXL,intravenously administered every 2 days for a total of 13 treatments,DTXL-DPN induced tumor regression and were associated to an overall 80%survival rate as opposed to a 30%survival rate for free-DTXL,at 120 *** untreated mice succumbed before 90 ***,this data demonstrates that vascular confined multi-passage DPN,biomimicking the behavior of circulating platelets,can efficiently deliver chemotherapeutic molecules to malignant tissues and effectively treat orthotopic TNBC at minimal taxane doses.

关键词： hydrogel particles template strategy vascular targeting biomimicry cancer therapy

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Cable Length Estimation for a Hyper-Redundant Robot Based on Cable Hole Clearance Calculation 19

Cable Length Estimation for a Hyper-Redundant Robot Based on...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Li, Ziqing Deng, Jiangqin Zheng, Yang Liu, Chao Gu, Guoying Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China

ISBN: (纸本)9798350320695

For the cable-driven hyper-redundant robot, most of the current drive cable length estimation methods consider that the cable always passes through the center of the hole, and do not consider the effect of cable-hole clearance, resulting in a large motion error. In this paper, we propose a cable length estimating method by considering cable-hole clearance. Based on the simplified space model of the cable hole, it uses the recursive algorithm to obtain the approximate solution of the actual drive cable length. The algorithm can meet the requirements of real-time control while ensuring calculation accuracy. The correctness of the approximate solution is verified by using the interior point penalty function method. Taking a 24DoF hyper-redundant manipulator with joint angle closed-loop control as an example, the effectiveness of the proposed method is proved by comparing the theoretical calculation results with the actual drive cable length. © 2023 IEEE.

关键词： Real time control

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive Control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Yu, Guanfeng Zhang, Han Wang, Zehao Wang, Jingchuan Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities. © 2024 IEEE.

关键词： Iterative methods

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