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Switching fluctuation compensation of the multi-view optical positioning system under camera occlusion

Switching fluctuation compensation of the multi-view optical...

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

作者： Yu, Zhengjun Li, Shibo Hu, Ying Jin, Haiyang Yu, Gang Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen518055 China Shenzhen Broadcare Medical Robotics Co. Ltd

ISBN: (纸本)9781665436786

The advances of multi-view optical tracking technology led to the rise of image-guided robotic-assisted surgery. The positioning accuracy of multi-view system is extremely crucial in ensuring the safety of the surgery process. The calibration error and camera occlusion may lead to the system switching fluctuation problem, which affects the system stability and limits its usage in situations requiring high safety standards. In this paper, the direct linear transformation (DLT) method is applied to solve multi-view triangulation problem and the influence of the calibration parameter error on the measurement accuracy is analyzed in the semi-physical simulation environment. The results show that the system switching fluctuation has a great influence on the positioning accuracy of the system. In order to improve the measurement stability of the system under camera occlusion, this paper proposes an error compensation strategy based on neural network nonlinear fitting. The measurement data at different locations in the workspace are used as learning samples. The trained network model is used to predict the occlusion points of the system and the measurement results are compensated for errors. Finally, the effectiveness of the compensation method is verified by simulations and real experiments. © 2021 IEEE.

关键词： Cameras

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TactCapsNet: Tactile capsule network for object hardness recognition

TactCapsNet: Tactile capsule network for object hardness rec...

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

作者： Fang, Senlin Mi, Tingting Zhou, Zhenning Ye, Chaoxiang Liu, Chengliang Wu, Hancheng Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen518055 China Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (纸本)9781665436786

Hardness is one of the most essential tactile clues for robots to recognize objects. However, methods for robots to recognize hardness are limited. In this paper, based on the Capsule Network (CapsNet), we propose a novel tactile capsule network (TactCapsNet) for object hardness recognition. Specifically, we collect a tactile dataset on the silicone samples with three different shapes, and the silicone samples of each shape have thirteen hardness levels ranging from 0A (Shore A scale) to 60A at 5A intervals. Furthermore, we construct the tactile image as the input of the CapsNet to make full use of the spatio-temporal information of the tactile hardness dataset. The experimental results prove that the proposed approach achieves higher accuracy and quadratic weighted kappa (QWK) than support vector machine (SVM), long short-term memory (LSTM), convolutional neural network (CNN), and CapsNet. © 2021 IEEE.

关键词： Hardness

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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A method for recognition of dynamic hand gestures based on wrist tendon sounds 22

A method for recognition of dynamic hand gestures based on w...

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

作者： He, Bailin Wang, Can Wang, Hao Li, Mengyao Duan, Shengcai 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 Samsung Electronics 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

Hand gesture recognition are widely applied in game industry and rehabilitation engineering. Some recognition methods based on physiological data are attracting attention. In this paper, a novel method for dynamic hand gesture recognition based on sounds of wrist tendon is proposed. Bone conduction sensors which automatically filter the ambient noise is utilized to collect the wrist tendon sounds of three types of dynamic hand gestures. Continuous Wavelet Transform(CWT) is utilized extract the features of sounds and Support Vector machine(SVM) is utilized to train the classifier model. Five healthy subjects participated the experiment and the average test accuracy of three classes achieves 92.33%. The proposed method provides an effective perspective for hand gesture recognition. © 2021 IEEE.

关键词： Support vector machines

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A comprehensive channel and feature selection method for myoelectric pattern recognition 22

A comprehensive channel and feature selection method for myo...

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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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Hand motion recognition based on pressure distribution maps and LS-SVM

Hand motion recognition based on pressure distribution maps ...

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International Conference on Mechatronics and control (ICMC)

作者： Nan Li Shourong Wei Minfeng Wei Bo Liu Hong Huo Li Jiang National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing Aerospace Automatic Control Institute Beijing China State Key Laboratory of Robotics and system Harbin Institute of Technology Harbin China

ISBN: (纸本)9781479925391

This paper presents a novel hand motion recognition method to achieve the volitional control of a multi-DOF prosthetic hand. Based on the principle that the pressure distributions on the surface of forearm caused by the muscular activities are different when different hand motions are performed, a human-machine interface (HMI) composed of 32 force sensitive resistor (FSR) sensors, measurement unit and recognition unit is designed to measure and classify the pressure distribution maps (PDM) of 9 typical hand motions. The least-squares support vector machine (LS-SVM) is adopted as the pattern recognition algorithm to classify the selected movement modes. The multi-subject experiment results show that the method can identify each motion with high accuracy.

关键词： Accuracy Sensor arrays Prosthetic hand Thumb Support vector machines

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Informative Path Planning based on Global and Local Active Sensing for Environmental Field Mapping

Informative Path Planning based on Global and Local Active S...

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IEEE International Conference on Robotics and Biomimetics

作者： Jiahui Li Bingyu Yang Kaibo Yang Teng Li School of Control Science and Engineering Shandong University Jinan China School of Statistics Beijing Normal University Zhuhai China Key Laboratory of Machine Intelligence and System Control Ministry of Education of the People's Republic of China Jinan China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Mobile robots can reconstruct environmental fields through active sensing and autonomous navigation, so as to achieve online environmental monitoring. Active sensing enables determine the target sampling location by exploiting the critical information in the target monitored environments. The key information for active sensing is commonly determined by the objective function based on environmental field statistics. In this paper, a novel global and local informative path planning method based on Gaussian process (GP) and multivariate conditional mutual information (MCMI) is proposed, which can achieve effective and reliable execution of information-based active sensing and path planning. Experimental results demonstrate the performance of the proposed method for robotic mobile sensing and environmental field mapping.

关键词： Gaussian processes Robot sensing systems Linear programming Path planning Sensors Mobile robots Reliability Environmental monitoring Biomedical monitoring Mutual information

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Research on synergy based on correlation analysis of weighted samples of grasping action

Research on synergy based on correlation analysis of weighte...

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Chinese Automation Congress (CAC)

作者： Jianjun Yu Zihao Zhang Guoyu Zuo Gengyuan Liu Xuchen Li Beijing Key Laboratory of Computational Intelligence and Intelligent System College of Electronic and Control Engineering Beijing University of Technology Beijing China

ISBN: (纸本)9781665426480

The main research goal of underactuated manipulator is to reduce the number of controllers and improve the bionic ability. In this kind of research, underactuated hand design synergy is the mainstream research direction in recent years. Human hand synergy space is a parameterized representation of human hand motion based on a large number of human hand motion data. In the past synergy meta-analysis, samples were selected only based on grasping classification without considering people's daily habits, which led to the lack of bionic ability. In this paper, based on the most authoritative 33 kinds of grabbing classification, the samples are weighted and reconstructed according to the daily use habits; Principal component analysis is used to analyze the reconstructed samples, and the correlation between joints is calculated to obtain the synergy of human hand. The comparative experiments show that the underactuated transmission scheme based on the synergy design of reconstructed samples has higher similarity and stronger bionic ability than the ordinary sample scheme in most grasping scenes. On this basis, this paper studies the following ability between fingers through the calculation of correlation coefficient and clustering method, so as to further reduce the number of controllers.

关键词： Correlation coefficient Actuators Correlation Automation Clustering methods Grasping Aerospace electronics

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A method for generating large-scale high definition color-point map

A method for generating large-scale high definition color-po...

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

作者： Li, Yuxiao Wang, Can Chen, Fan Su, Zhilong Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence Synergic Systems Shenzhen Institutes of Advanced Technolog Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781728137261

We propose a method to reconstruct a High-Definition Color-Pointed map from the large-scale urban road scene. In contrast to prior methods, we collect the urban road data under the severe traffic conditions and several kilometers long data sets. In our High-Definition Color-Pointed map, we can clearly see the lane surface and surrounding environment. Moreover, our maps are collected in a high speed of 40km/h, which greatly improved the practicality of the whole system. The High-Definition Color-Pointed map can be used in perception, localization and automatic navigation in driverless cars, drones and smart city management. Images, lidar and gnss best poses are collected as the raw data. We use interpolation method to process the raw data, and use our algorithm to translate the Lidar poses into the images collected time. To detect the dynamic obstacle, we use the fast neural framework YOLOv2. Our method, Dislocation Projection, can solve the spare points problems. Our algorithm was evaluated on wide roads and narrow streets. The experimental results exhibited the effectiveness of the proposed approach. © 2019 IEEE.

关键词： Optical radar

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A one-step pseudolinear kalman filter for invasive target tracking in three-dimensional space

A one-step pseudolinear kalman filter for invasive target tr...

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

作者： Zhang, Ying Liang, Rui Xu, Sheng Zhang, Liyuan Zhang, Ye Xiao, Dandan State Grid Tianjin Electric Power Company City West Power Supply Branch Tianjin300190 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9781665436786

This work studies the characteristics of the 3-dimensional (3D) pseudolinear Kalman filter (PLKF) proposed in the previous work [1] for angle-of-arrival (AOA) target tracking in the 3D space. The previous two-step 3D PLKF contains an xy-PLKF and a z-PLKF. This paper develops a one-step PLKF algorithm, which has low computational complexity. The estimation performance analysis of these two different PLKFs is provided. The one-step PLKF sacrifices the estimation accuracy to acquire a low computational complexity. In the distributed target tracking problem, the one-step PLKF can save a lot of communication costs compared with the two-step one. Furthermore, the stability of two PLKFs are also been simply proven. Simulation examples verify the effectiveness of the proposed one-step 3D PLKF to track an invasive target. Besides, the difference between the two PLKFs based on the theoretical analysis is also demonstrated by the simulation examples. © 2021 IEEE.

关键词： Target tracking

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