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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mohamad R. Mohamadi Vahid Akbari Omid Mahdizadeh Mahdi Nabipour S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

Exoskeletons are used in different applications including the area of physical therapy in order to facilitate the patient's exercises and as an assisting technology to assist the elderly carry out their ordinary activities. At the beginning of this paper, the RoboWalk assistive device is introduced. Before constructing the system, the performance of the device must be analyzed through different simulations. Hence, the dynamics of the human and RoboWalk are then obtained using the Newton-Euler (NE) and the Recursive Newton Euler Algorithm (RNEA). The obtained models are then augmented to the human model to estimate the RoboWalkjoint forces and torques, and those of the human model. then, RoboWalk is imported to the human model in Opensim software and the augmented model is obtained by defining some constraints and joint models. Controllers are then designed for the human and Robo Walk in Opensim. In the next step, The NE and RNEA models are then compared to the models obtained from Opensim software using the same gait data. It is shown that the NE and RNEA methods match very closely and both of the models possess the same behavior as the Opensim model.

关键词： Mathematical model Robots Force Actuators Footwear Knee Dynamics

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Haptic and visual enhance-based motor imagery BCI for rehabilitation lower-limb exoskeleton

Haptic and visual enhance-based motor imagery BCI for rehabi...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Duan, Shengcai Wang, Can Li, Mengyao Long, Xingguo Wu, Xinyu Feng, Wei Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China University of Chinese Academy of Sciences China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781728163215

The motor imagery (MI) based on electroencephalogram (EEG) via non-invasive Brain Computer Interface (BCI) is a promising interactive method to provide effective communication between the disabled and rehabilitation robotic device. Interactive efficiency of MI-based BCI largely relies on the performance of subject's motor imagery. In this work, we proposed a simple and effective paradigm based on visual and haptic modalities for a high-quality initialized and calibrated MI-BCI model. Five healthy male subjects participated in motor imagery experiments with two paradigms. The proposed paradigm utilized mixed cues based on the visual and haptic modalities where the haptic cues were provided by the mini vibration motors, and a traditional paradigm utilized the ordinary arrow visual cues. The analysis of the topographic maps was conducted to illustrate the differences of the EEG in both paradigms. The average classification accuracy of motor imagery in the proposed paradigm improved about 14% compared to the traditional paradigm. Furthermore, a subject completed the qualitative verification experiment of the trained model on a rehabilitation lower-limb exoskeleton which proved the feasibility of the proposed paradigm. © 2019 IEEE.

关键词： Brain computer interface

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Visual SLAM based on geometric cluster matching

Visual SLAM based on geometric cluster matching

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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Tian, Chaoran Ou, Yongsheng Qu, Yangyang Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University OfChinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes OfAdvanced Technology Chinese Academy OfSciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781728137261

The approach of feature-based visual SLAM is very popular in Micro Aerial Vehicle (MAV) navigation and wheeled mobile robot (WMR) navigation. Most modern feature-based visual SLAM frameworks extract a fixed number of feature points and then match the feature points by brute force or adopt Fast Library for Approximate Nearest Neighbors (FLANN). The features' extracting and matching processes will determine the localization accuracy and mapping quality significantly. In this paper, we propose a feature matching algorithm for the robot equipped with a binocular camera, which provides accurate real-time localization performance and robustness. In our feature matching method, both the geometric relationship of image feature points and the similarity of descriptor are considered. This paper presents a visual SLAM framework based on geometric cluster matching and the effectiveness of the proposed method is verified by practical experiments. © 2019 IEEE.

关键词： Mobile robots

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Fuzzy Adaptive Control-based Real-time Obstacle Avoidance under Uncertain Perturbations

Fuzzy Adaptive Control-based Real-time Obstacle Avoidance un...

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International Conference on advanced robotics and Mechatronics (ICARM)

作者： Yingbai Hu Guang Chen Longbin Zhang Hang Su Mengyao Li Yunus Schmirander Hu Cao Alois Knoll Chair of Robotics Artificial Intelligence and Realtime Systems Technical University of Munich Munich Germany College of Automotive Engineering Tongji University Shanghai China KTH MoveAbility Lab KTH Royal Institute of Technology Stockholm Sweden Politecnico di Milano Milano Italy Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9781728164793

ISBN: (纸本)9781728164809

Dynamic Movement Primitives (DMPs) framework is a powerful approach to imitate motor skills, which has outstanding characteristics, such as convergence to the goal position and good imitation performance. Considering complex motion scenes of manipulators, such as changing the goal position or adding obstacles, the original DMPs framework is not sufficient for the requirements. In this paper, we propose a learning control-based hierarchical control strategy to adapt to new goal positions and avoid obstacles: the high-level learning scheme is targeted at imitating the motor skill and generating the optimization trajectory for obstacle avoidance; the lower-level control scheme focuses on the safety and stability of the robot's movement with unknown disturbances. Firstly, the enhanced DMPs framework is presented to imitate the trajectory from human demonstrations, where the novel DMPs can adapt to new goal position with the changing goal, and avoid single or multiple obstacles. Then, the fuzzy adaptive control method is employed to control redundant manipulators, where the fuzzy logic system (FLS) is incorporated to approximate an unknown nonlinear function term of the unknown disturbance. Finally, the effectiveness of the proposed learning-control strategy is demonstrated with simulation results. The results show that the developed hierarchical strategy has good performance for new goal adaptation and obstacle avoidance.

关键词： Collision avoidance Trajectory Manipulator dynamics Nonlinear dynamical systems Adaptive control

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RoboWalk Multiple-Sensor and Multipolar Data Fusion

RoboWalk Multiple-Sensor and Multipolar Data Fusion

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Omid Mahdizadeh Vahid Akbari S. Ali A. Moosavian Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology. Tehran Iran

ISBN: (数字)9781728166049

ISBN: (纸本)9781728166056

RoboWalk is a two-legged rehabilitation assisting robot, which helps users by carrying a portion of the weight. In this paper, we propose an algorithm to correct the attitude and position error by means of an Adaptive Root Square Unscented Kalman Filter. To this end, the IMU and encoders are used to determine the robot kinematic configuration, but since there is no solid connection between the ground and the feet, the sensor's data may not lead to exact positioning configuration. Therefore, a new approach for estimating the position of the feet and the seat is presented. The method is based on using the standing foot IMU, and related encoders to obtain the seat position. Then, the obtained result is compared to the seat IMU and correcting the position. Next, the corrected position and the swing leg encoders are used to obtain the swing foot position, which is compared to the corresponding IMU, to modify and yield all corrected positions. Describing the proposed method, it is then implemented, and the results will be discussed.

关键词： Mathematical model Robot sensing systems Estimation Robot kinematics Foot

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A lightweight soft exoskeleton in lower limb assistance

A lightweight soft exoskeleton in lower limb assistance

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Chinese Automation Congress (CAC)

作者： Yu Zhang Zhuo Wang Chunjie Chen Tao Fang Ruimei Sun Yanjie Li School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China ShenZhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China BeiJing Aerospace Wanyuan Science Technology Co. Ltd. Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

The soft exoskeleton is a wearable robot which is functioned to improve the capacity of human walking or loading. The metabolic of human is increase with the additional load, one integrated design method is used to reduce this effect in this paper. Meanwhile, in order to enhance the convenience and decrease the disturbance to wearer, the wireless module is used to replace the signal line. The nonlinear characteristics and uncertainty of flexible material make the control of soft exoskeleton system be a challenge, a switching controller is proposed to deal with this problem in this paper. It consists of Iterative learning control (ILC) based stable controller and admittance control based unstable controller, functioned with wearers walking stable and not. An experiment of force tracking is conducted to verify the controller performance in this paper, and the result demonstrate that the tracking is well after 20 iteration. In order to evaluate the performance of assistance of soft exoskeleton, five health adult male take part in metabolic experiment By compare the metabolic rate between the wear soft exoskeleton and not wear, the metabolic rate are decrease 7.33%, 14.56% and 10.45% with the walking speed of 3km/h, 5km/h and 7km/h, which are corresponding absolute values decrease of 0.46W/kg, 1.60W/kg and 1.21W/kg respectively.

关键词： AC motors Mechanical cables Wireless communication Pulleys Microprocessors Micromechanical devices Germanium

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Diffusive nonreciprocity and thermal diode

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Physical Review B 2021年第1期103卷 014307-014307页

作者： Ying Li Jiaxin Li Minghong Qi Cheng-Wei Qiu Hongsheng Chen Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Zhejiang University Hangzhou 310027 China International Joint Innovation Center ZJU-UIUC Institute The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 Singapore State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China

Wave propagation and diffusion in linear materials preserve local reciprocity in terms of a symmetric Green's function. For wave propagations, the relation between the fields entering and leaving a system is more relevant than the detailed information about the fields inside it. In such cases, the global reciprocity of the scattering off a system through several ports is more important, which is defined as the symmetric transmission between the scattering channels. When a two-port system supports nonreciprocal (electromagnetic, acoustic) wave propagation, it is a (optical, phonon) diode directly following the definition. However, to date no concrete definition or discussion has been made on the global reciprocity of diffusive processes through a multiple-port system. It thus remains unclear what are the differences and relations between the three concepts, namely, local nonreciprocity, global nonreciprocity, and diode effect in diffusion. Here, we provide theoretical analysis on the frequency-domain Green's function and define the global reciprocity of heat diffusion through a two-port system, which has a different setup from that of a thermal diode. We further prove the equivalence between a heat transfer system with broken steady-state global reciprocity and a thermal diode, assuming no temperature-dependent heat generation. The validities of some typical mechanisms in breaking the diffusive reciprocity and making a thermal diode have been discussed. Our results set a general background for future studies on symmetric and asymmetric diffusive processes.

关键词： Diffusion Heat transfer Metamaterials Diodes Green's function methods

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Real-world Robot Reaching Skill Learning Based on Deep Reinforcement Learning

Real-world Robot Reaching Skill Learning Based on Deep Reinf...

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第32届中国控制与决策会议

作者： Naijun Liu Tao Lu Yinghao Cai Rui Wang Shuo Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences University of Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Center for Excellence in Brain Science and Intelligence Technology of the Chinese Academy of Sciences

Traditional programming method can achieve certain manipulation tasks with the assumption that robot environment is known and ***,with robots gradually applied in more domains,robots often encounter working scenes which are complicated,unpredictable,and *** overcome the limitation of traditional programming method,in this paper,we apply deep reinforcement learning(DRL) method to train robot agent to obtain skill *** policy trained with DRL on real-world robot is time-consuming and costly,we propose a novel and simple learning paradigm with the aim of training physical robot ***,our method train a virtual agent in an simulated environment to reach random target position from random initial ***,virtual agent trajectory sequence obtained with the trained policy,is transformed to real-world robot command with coordinate transformation to control robot performing reaching *** show that the proposed method can obtain self-adaptive reaching policy with low training cost,which is of great benefits for developing intelligent and robust robot manipulation skill system.

关键词： Robot reaching skill learning deep reinforcement learning

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An Image segmentation method by multi-scale local thresholding based on class uncertainty theory

An Image segmentation method by multi-scale local thresholdi...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Zhou, Likai Jiang, Yuyang Liang, Guoyuan Wu, Xinyu Zhu, Jiafeng Xiang, Huaikun Shenzhen Institutes of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences China School of Automotive and Transportation Engineering Shenzhen Polytechnic Shenzhen Guangdong Province China School of Math Sun Yat-sen University Guangzhou Guangdong Province China

ISBN: (纸本)9781728163215

Image segmentation is one of the most important core technologies in the field of image processing and computer vision, which has lots of applications specifically in medical image analysis. Due to medical imaging mechanism, medical images usually suffer from heavy noises, uneven intensity distribution and fuzzy boundaries between biological tissues. That makes classical segmentation methods based on global or local thresholding difficult to get accurate results. This paper proposes an image segmentation method by multi-scale local thresholding based on class uncertainty theory. Firstly, the original image is divided into a set of sub-regions with different scales by using a multi-layer pyramid structure. Secondly, the energy function with inequality constraints is constructed based on class uncertainty and region uniformity. Then by an iterative process, the optimal local threshold for each sub-region are calculated by an optimization algorithm for each layer until the final optimal threshold mask is determined for image segmentation. Experimental results verify that the proposed method can effectively eliminate the interferences caused by image noises, intensity unevenness and fuzzy boundaries, and preserve details of object structure while segmenting the object from the background. Segmentation results demonstrate the superior performance of the proposed method by comparison with supervised range-constrained thresholding methods (RCOtsu), classical global/local Otsu method, and the minimization of homogeneity- and uncertainty-based energy method (MHUE). © 2019 IEEE.

关键词： Image segmentation

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BTI Aging Monitoring based on SRAM Start-up Behavior

BTI Aging Monitoring based on SRAM Start-up Behavior

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Asian Test Symposium (ATS)

作者： Shengyu Duan Peng Wang Gaole Sai School of Computer Engineering and Science Shanghai University Shanghai China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (数字)9781728174679

ISBN: (纸本)9781728174686

Bias Temperature Instability (BTI) is one of the dominant CMOS aging mechanisms. It causes time-dependent variation, threatening circuit lifetime reliability. BTI-induced circuit errors are not detectable at the fabrication stage. On-line monitoring schemes are therefore necessary to capture the degradations during the operational time. Traditional aging monitoring techniques exhibit high implementation complexity and low stability. In this paper, we propose a BTI monitoring approach by simply tracking the start-up behavior of SRAM cells. SRAM is a widely used on-chip device in many applications. We study the impact of BTI for SRAM start-up values and age some cells in a manipulated manner. The BTI degradation is evaluated based on the number of SRAM cells starting with a certain value. This technique can be used to estimate the degradation for on-chip logic circuits without introducing additional circuitry, and thus has very low implementation complexity. We use an SRAM array with 1024 cells to estimate the degradations for multiple logic circuits, and show the average mean absolute percentage error as 8.48%. In addition, this technique is robust considering process, voltage and temperature variations.

关键词： Degradation Monitoring Logic circuits Transistors SRAM cells Aging System-on-chip

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