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

作者： Wang, Shun Guo, Qingqiang Xu, Sheng Su, Dan School of Control Science and Engineering Shandong University Shandong Jinan250061 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jinan250102 China Orbbec Inc. Shenzhen518057 China

ISBN: (纸本)9781665436786

This paper proposes a new strategy for moving target detection and localization based on monocular vision. Firstly, to detect a moving target with large displacement and high speed accurately, two consecutive video images captured by a monocular camera are preprocessed using the enhancement and denoising methods. Then, the optical flow representing motion information is calculated iteratively by the modified Lucas-Kanade optical flow method. Secondly, a new interest region extraction method is developed to overcome the negative impacts caused by the noises in the background. Specifically, this proposed method combines a two-level image segmentation strategy from coarse to fine, including median filtering, two-direction dynamic threshold segmentation, the Otsu method, and morphological processing. Thirdly, a low computational cost target localization algorithm is proposed based on pin-hole imaging theory. Besides, it only uses two-dimensional image and camera parameters to obtain the moving target's position in the three-dimensional space. Finally, experimental results show that the proposed strategy can effectively eliminate noise interferences and realize moving target detection, extraction, and localization. © 2021 IEEE.

关键词： Image segmentation

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A Deep Siamese Neural Network N-Shot Learning Approach for the Recognition of Chinese Calligraphy

SSRN

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SSRN 2022年

作者： Zhou, Zhaokun Wang, Weijun Ou, Yuhao Che, Qishu Feng, Wei Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Guangzhou Institute of Advanced Technology Chinese Academy of Sciences Guangdong Guangzhou511458 China University of Chinese Academy of Sciences Guangdong Shenzhen518055 China

The forms of Chinese calligraphic characters vary considerably, posing a challenge even for a typical educated Chinese to read. The total number of characters is in the excess of ten thousand, many of which have small numbers of samples surviving to date. Thus, Chinese calligraphy recognition is a unique challenge for the state-of-the art deep-learning algorithms that require large training datasets to accurately categorize. Here we present a novel deep-convolutional Siamese Neural Network (SNN) based architecture that finishes training in one day on a single RTX 2080 Ti graphics card while reaching an accuracy of 95.0% on a vast set of more than 6000 Chinese characters. We found that, after image pre-processing and setting the optimized SNN parameters, our recognition algorithm (i) is light weight, (ii) trains with small numbers of samples, achieving few-/one-shot learning (iii) recognizes a new character that is not present in the training set and (iv) includes the new character in the dictionary so the dictionary is continually expanded. Further work on the improvement of our method is also proposed including the localization of multiple tokens in an image to further automate detections and word prediction with RNNs to boost categorization accuracy. © 2022, The Authors. All rights reserved.

关键词： Optical character recognition

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An Improved UAV Path Optimization Algorithm for Target Accurately and Quickly Localization

An Improved UAV Path Optimization Algorithm for Target Accur...

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2021 International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2021

作者： Liang, Rui Wu, Kai Xu, Sheng Xu, Tiantian Ma, Xiaoyi Fu, Lianyu City West Power Supply Branch State Grid Tianjin Electric Power Company Tianjin China Shenzhen Institute of Advanced Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen China Shenzhen Institute of Advanced Technology Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China State Grid Tianjin Information Telecommunication Company Tianjin China

ISBN: (纸本)9781665402453

Angle-of-arrival (AOA) target localization using the unmanned aerial vehicle (UAV) has been widely applied in many practical applications. To localize an invasive target quickly and accurately, both the estimation and UAV path optimization algorithms are required. This paper focuses on developing a path optimization method to improve the target estimation performance. Firstly, the problem formulation of AOA target localization is introduced. Secondly, the classical pseudolinear Kalman filter (PLKF) and the gradient-based path optimization are presented. Thirdly, we analyze the problems that existed in the previous methods and propose an improved gradient-descent path optimization algorithm combined with a simple grid search method. Finally, the simulation examples verify the effectiveness of the proposed methods. © 2021 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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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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Crossbreeding in random forest

arXiv

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arXiv 2021年

作者： Nadi, Abolfazl Moradi, Hadi Taheri, Khalil Advanced Robotics and Intelligent Systems Laboratory School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran11155-4563 Iran SKKU Suwon16419 Korea Republic of

Ensemble learning methods are designed to benefit from multiple learning algorithms for better predictive performance. The tradeoff of this improved performance is slower speed and larger size of ensemble learning systems compared to single learning systems. In this paper, we present a novel approach to deal with this problem in Random Forest (RF) as one of the most powerful ensemble methods. The method is based on crossbreeding of the best tree branches to increase the performance of RF in space and speed while keeping the performance in the classification measures. The proposed approach has been tested on a group of synthetic and real datasets and compared to the standard RF approach. Several evaluations have been conducted to determine the effects of the Crossbred RF (CRF) on the accuracy and the number of trees in a forest. The results show better performance of CRF compared to RF. © 2021, CC BY-NC-ND.

关键词： Learning systems

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Accurate Parameter Estimation of Time-varying Nuclear Radiation Field with Mobile Sensors

Accurate Parameter Estimation of Time-varying Nuclear Radiat...

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第40届中国控制会议

作者： Bo Chen Zhicheng Li Zaiyue Yang Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering and the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology

In this paper, the optimization strategy of mobile sensors and the parameter estimation of time-varying nuclear radiation field are investigated. Based on the measurement model with white Gaussian noise, Fisher information matrix is derived as an information metric. At each time step, finding the best mobile sensor coordinates that contain the amount of maximal information in the 4-Dimension space is formulated as a constrained nonlinear optimization problem, which is able to minimize the trace of Cramer-Rao Lower Bound. Further, an efficient heuristic algorithm called Augmented Lagrangian Genetic Algorithm is adopted to solve the above optimization problem. Then, the parameters of nuclear radiation field are estimated by a maximum likelihood estimator. The proposed sensor coordinates moving strategy has better estimation performance than random coordinates strategy, which is demonstrated via simulation results.

关键词： Optimal sensor coordinates Fisher information matrix(FIM) Cramer-Rao Lower Bound(CRLB) Augmented Lagrangian Genetic Algorithm(ALGA) Maximum likelihood estimate(MLE)

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Distributed Vehicle Platoon Control with Leader Selection Strategy

Distributed Vehicle Platoon Control with Leader Selection St...

引用

第40届中国控制会议

作者： Zikai Ouyang Zhicheng Li Shibo Chen Zaiyue Yang Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering and the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology

This paper investigates the control problem of vehicle platoon with leader selection strategy. The current research on vehicle platoon control is based on the leader-follower communication structure. Under such structure, each follower tracks the state of its front vehicle to maintain a proper distance and form a platoon. However, the disadvantage of this fixed communication structure is that followers are short of capacity of resisting disturbance when the first vehicle(FV) of platoon is disturbed. To solve this problem, a vehicle platoon model where each follower is able to take any front vehicle as its leader is proposed. Based on this model, the corresponding controller and leader selection strategy are designed. That is, first, a controller considering the string stability of vehicle platoon with various communication topologies is designed;then, each follower changes its connecting vehicle in the communication link to reduce the impact of disturbance on FV when FV suddenly slows down or speeds up. The simulation results show the effectiveness of the control method and the strategy.

关键词： Vehicle platoon leader selection strategy distributed control

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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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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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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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