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22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Li, Mengyao Ma, Yue Zheng, Liangsheng Wang, Can Feng, Wei Wu, Xinyu Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781728162676

The advent of myoelectric control schemes provides promising chances for locomotion empowerment and restoration of those with disabilities. Despite substantial efforts have been made into advancing sEMG-based motion recognition, it may be a little tricky to determine appropriate muscles and features for people with muscle disorders or different muscle use preferences. To mitigate it, an advantageous sEMG channel and feature selection method based on ReliefF algorithm was proposed. Related experiments were conducted on a eight able-bodied subject database to showcase the feasibility and efficiency of the proposed approach, that is, considerably high classification performance was maintained with the original feature set reduced by more than half. Ulteriorly, we also investigated the influences of different number of neighbors or features on classification accuracy for ascertaining the optimal values. The strengths of our proposed method lie in not only customizing channel and feature selection for individual users, but also offering preliminary insight for a general mapping mechanism between human muscles and corresponding motions. © 2021 IEEE.

关键词： Feature Selection

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NeRF in robotics: A Survey

arXiv

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arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in robotics and The Advance of NeRF in robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： robotics

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The Intelligent Power Wheelchair Upgrade Kit

The Intelligent Power Wheelchair Upgrade Kit

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IEEE International Conference on Robotic Computing (IRC)

作者： Jesse Leaman Hung Manh La Advanced Robotics and Automation (ARA) Laboratory University of Nevada Reno NV USA

ISBN: (数字)9781728152370

ISBN: (纸本)9781728152387

This paper presents an update on the research and development of the Intelligent Power Wheelchair (IPW) upgrade kit. First, we review the last three years of trials, then we describe the improvements proposed for the next prototype. The 2020 IPW edition is designed to be more light weight, modular, and multi-functional than it's predecessor. The assembly process has been streamlined, and there is now greater ability to tailor the system to the needs of the individual user. The brand new, self-leveling scanner has broader applications as an aid for people with visual impairment. Keywords: Smart Wheelchair, Human Trials.

关键词： Visualization Wheelchairs Prototypes Tools Robot sensing systems Collision avoidance Research and development

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MCC-EKF for Autonomous Car Security

MCC-EKF for Autonomous Car Security

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IEEE International Conference on Robotic Computing (IRC)

作者： Ashutosh Singandhupe Hung Manh La Advanced Robotics and Automation (ARA) Laboratory University of Nevada Reno NV USA

ISBN: (数字)9781728152370

ISBN: (纸本)9781728152387

This work attempts to answer two problems. (1) Can we use the odometry information from two different Simultaneous Localization And Mapping (SLAM) algorithms to get a better estimate of the odometry? and (2) What if one of the SLAM algorithms gets affected by shot noise or by attack vectors, and can we resolve this situation? To answer the first question we focus on fusing odometries from Lidar-based SLAM and Visual-based SLAM using the Extended Kalman Filter (EKF) algorithm. The second question is answered by introducing the Maximum Correntropy Criterion - Extended Kalman Filter (MCC-EKF), which assists in removing/minimizing shot noise or attack vectors injected into the system. We manually simulate the shot noise and see how our system responds to the noise vectors. We also evaluate our approach on KITTI dataset for self-driving cars.

关键词： Simultaneous localization and mapping Autonomous systems Trajectory Autonomous automobiles Security Kalman filters Multi-robot systems

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Impedance control for a novel composite modular lower-limb hemiplegic exoskeleton

Impedance control for a novel composite modular lower-limb h...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Bao, Ruoyu Li, Pengbo He, Bailin Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical and Automation Engineering Chinese University of Hong Kong College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi'an710021 China

ISBN: (纸本)9781665436786

This paper proposes a control scheme based on impedance control for the smoothing control of the operating movements of a lower-limb hemiplegic exoskeleton robot on the basis of a new composite modular lower-limb hemiplegic ex-oskeleton(CMLHE) structure. The CMLHE has good structural performance and can be used in the rehabilitation of patients with hemiplegia caused by stroke and other diseases. At the same time, the smoothing control by means of impedance control ensures that patients with lower limb hemiplegia can use the CMLHE to achieve smooth walking movements without additional injuries caused by the CMLHE during the rehabilitation training. This paper analyses the performance of this CMLHE robot based on walking movements and demonstrates through kinematic and kinetic modelling and simulation that the impedance control scheme of this CMLHE robot is feasible and effective and can be more widely used in the rehabilitation training of patients with lower limb hemiplegia. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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A modular rehabilitation lower limb exoskeleton for stroke patients with hemiplegia

A modular rehabilitation lower limb exoskeleton for stroke p...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Li, Pengbo Wei, Wenhao Bao, Ruoyu He, Bailin Su, Zhilong Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Department of Mechanical and Automation Engineering The Chinese University of Hong Kong College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi'an710021 China

ISBN: (纸本)9781665436786

A modular rehabilitation exoskeleton robot for hemiplegic patients (SIAT-H) is created in this paper. The design of the exoskeleton is based on the gait analysis of hemiplegic patients and the movement data of healthy people. Through the motion capture experiments at different speeds, the walking style of patients with hemiplegia is understood. A modular exoskeleton robot, including an independent hip joint, knee joint and ankle joint, is designed. The mechanical structure which is optimized based on the physiological characteristics of human body would not cause additional damage to the joints during walking. In order to ensure the reliability of use, the structural strength is also considered. The kinematics relationship is verified by comparison of simulation data and calculated data. In the end, we made an experimental prototype, and the wearing experiment verified the reliability of the mechanism. © 2021 IEEE.

关键词： Exoskeleton (robotics)

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Compact Multiple Functional Integrated Medical Robotic End-Effector for Neurosurgery*

Compact Multiple Functional Integrated Medical Robotic End-E...

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WRC Symposium on advanced robotics and automation (WRC SARA)

作者： Yinjia Zhang Weihan Li Haotian Wang Xudong Ma Qian Yang Jie Tang Yuanzheng Hou Yida David Hu Changsheng Li Wenyong Liu Junchen Wang Bai-Quan Su Medical Robotics Laboratory School of Intellgent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China Graduate School of Engineering The University of Tokyo Tokyo Japan Department of Neurosurgery Xuanwu Hospital Capital Medical University Beijing China Harvard Medical School Brigham and Women’s Hospital Boston MA USA School of Mechatronical Engineering Beijing Institute of Technology Beijing China Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

In neurosurgery, surgeons use single-function surgical tools such as aspirator and electric-coagulation cutters to deal with blood vessel bleeding. Compared with multi-functional surgical tools, the surgical efficiency of using single-function tools is lower. In this paper, a multiple functional integrated medical robotic end-effector which integrates CCD imaging, electric-coagulation and suction is designed. The end-effector can be installed at the end of the serial robotic arm. The CAD model of the end-effector was constructed, and the motion analysis is carried out. The end-effector is proved to be effective by three experiments. The operator can use the design to suction blood, spotting of bleeding spots, and electric-coagulation lesion. In operations, there is no need to change the surgical tools, improve the efficiency of the operation.

关键词： Charge coupled devices Solid modeling Medical robotics Design automation Instruments Prototypes Three-dimensional printing

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Design and preliminary testing of a piezoelectric-based sole energy harvester

Design and preliminary testing of a piezoelectric-based sole...

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IEEE International Conference on robotics and Biomimetics

作者： Yidi Wang Xuan Zhao Qiuyu Shi Haisu Liao Xinyu Wu Fei Gao Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China

ISBN: (纸本)9781665481106

Harvesting energy from the human body to replenish existing energy sources is receiving substantial attention. Recently scientists have been focusing on harvesting biomechanical energy from human feet during walking. This paper develops a piezoelectric-based sole energy harvester that is designed to be worn on the bottom of shoes to harvest energy, thus powering wearable electronic devices. Specifically, a cam with piezoelectric(PZT) stacks is mounted on the heel to scavenge energy during the heel strike. The cam can change the input's direction from the vertical direction to the horizontal direction. In addition, the output power of this part can be optimized or improved by generating a specified cam profile. A bimorph piezoelectric plate is installed on the forefoot to convert the toes' bending deformation into electricity. Herein, piezoelectric Macro Fiber Composites (MFC) are employed to capture the large deformation. Preliminary testing on a healthy subject is conducted to validate this design. The average power output of the harvester is 8.83 m W.

关键词： Legged locomotion Biomechanics Wearable computers Bending Optical fiber devices Piezoelectric devices Optical fiber testing

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Modeling Neural Representation of Social Recognition Information with Recurrent Neural Networks

Modeling Neural Representation of Social Recognition Informa...

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IEEE/ICME International Conference on Complex Medical Engineering, CME

作者： Fei Song Xinnian Wang Yang Zhan Fengzhen Tang Bailu Si 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 University of Chinese Academy of Sciences Beijing China Division of Life Science and Medicine School of Life Sciences University of Science and Technology of China Hefei China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Systems Science Beijing Normal University Beijing China Chinese Institute for Brain Research Beijing China

ISBN: (数字)9798350316117

ISBN: (纸本)9798350316124

Social recognition, the ability to differentiate between familiar and unfamiliar individuals, is crucial for animals' survival and reproduction. Neuroscience research has predominantly focused on investigating the brain regions and circuits that regulate social recognition. However, a lingering question pertains to the precise mechanisms underlying the social recognition process. To address this question, we employed a recurrent neural network (RNN) to determine whether an agent can recognize familiar individuals without involving higher-level decision-making processes. This approach takes into consideration that animal behavioral performance may not directly mirror complex cognitive functions. The RNN was trained using the full-FORCE learning paradigm. Our simulation results revealed three distinct subsets of neurons with specific functions: one dedicated to representing novel individuals and two others representing the same social individual in both unfamiliar and familiar states. We propose a hypothesis regarding the potential memory computing processes involved in these operations.

关键词： Analytical models Recurrent neural networks Neuroscience Animals Computational modeling Simulation Neurons

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2D Laser and 3D Camera Data Integration and Filtering for Human Trajectory Tracking

2D Laser and 3D Camera Data Integration and Filtering for Hu...

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IEEE/SICE International Symposium on System Integration

作者： Hamed Bozorgi Xuan Tung Truong Hung Manh La Trung Dung Ngo The More-Than-One Robotics Lab Faculty of Sustainable Design Engineering University of Prince Edward Island 550 University Ave Charlottetown Prince Edward Island Canada Advanced Robotics and Automation (ARA) Laboratory University of Nevada Reno USA

ISBN: (数字)9781728176581

ISBN: (纸本)9781728176598

This paper addresses a robust human trajectory tracking method through the data integration of 2D laser scanner and 3D camera. Mapping the deep learning-based 3D camera human detection onto the point cloud of the depth information to build up the 3D bounding box-represented human and using the state-of-the-art 2D laser-based leg detection are the main data streams of the human tracking system. The human-oriented global nearest neighbour (HOGNN) data association, inspired from the Hall's proxemics, was developed to improve both the 3D camera-based and 2D laser-based human detection techniques. The dual Kalman filters are employed to track the human trajectory in parallel. The integration of the 3D camera-based and 2D laser-based human tracking is the key function of the system providing the real-time feedback for both the HOGNN to reduce false-positives of the camera-based and laser-based human detection and the Kalman filter to enhance the quality of the human trajectory tracking under uncertain environmental conditions. We implemented the sensor integration on ROS and validated it through real-world experiments.

关键词： Three-dimensional displays Trajectory tracking Two dimensional displays Lasers Data integration Cameras Kalman filters

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