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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Zhang, Liming Zhou, Xin Zhu, Baixian Wang, Can 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-Synergy Systems Shenzhen Institutes of Advanced Technology China University of Science and Technology of China China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In this work, we propose a new image feature extraction network for 6D pose estimation tasks. The majority of existing 6D pose estimation networks are based on the RGBD input, which is the fusion of images and point clouds. They are mainly working on keypoint extraction, point cloud feature extraction, and other tasks, however, image features, on the other hand, mainly rely on CNN networks that are currently advanced. With the development of Vision Transformer in the field of computer vision, the results on ImageNet demonstrate its benefit of extracting global features, and we see new directions that the Transformers can bring to the area of image feature extraction. ICTC is a Transformer paired with a CNN network that fuses the retrieved global features into each pixel and then does local feature extraction. This provides greater robustness to 6D pose estimation In complex situations such as shifting lighting conditions and object occlusion. Our method achieves 96% accuracy using the average ADD metric on the LineMOD dataset, demonstrating our method's effectiveness. © 2022 IEEE.

关键词： Feature extraction

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A Survey of Deep Learning-based Hand Pose Estimation

A Survey of Deep Learning-based Hand Pose Estimation

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IEEE International Conference on Cloud Computing and Intelligence systems (CCIS)

作者： Shuaibing Wang Shunli Wang HaoPeng Kuang Fang Li Ziyun Qian Mingcheng Li Lihua Zhang Academy for Engineering & Technology Fudan University Engineering Research Center of AI and Robotics Ministry of Education China Jilin Provincial Key Laboratory of Intelligence Science & Engineering China AI & Unmanned Systems Engineering Research Center of Jilin Province China

ISBN: (纸本)9781665456579

Hand pose estimation is one of the representative tasks in computer vision. Solving the hand pose estimation problem is essential for various fields such as virtual reality, augmented reality, mixed reality, and human-computer interaction. Due to the significant development of deep learning techniques, the hand pose estimation task has reached significant performance on many hand pose estimation datasets. However, the hand pose estimation task still faces many challenges due to the lack of large-scale labeled data, severe occlusion, low hand resolution, and background clutter. To better understand the hand pose estimation task, this paper presents a comprehensive survey of outstanding papers over the last five years. The paper first introduces 19 common hand pose estimation datasets, then extensively discusses some of the mainstream approaches in hand pose estimation, including fully supervised, semi-supervised, weakly supervised, and self-supervised learning methods. Finally, we extensively discuss the future evolution trends of hand pose estimation.

关键词： Human computer interaction Computer vision Solid modeling Pose estimation Supervised learning Mixed reality Self-supervised learning

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A Novel Bio-Inspired Quadruped Crawling Robot with Movable Waist

A Novel Bio-Inspired Quadruped Crawling Robot with Movable W...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Ruiqin Wang Hao Wu Jian S. Dai The School of Mechanical Engineering Hebei University of Technology Tianjin China School of Mechanical Engineering Hebei University of Technology Tianjin China The Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and Technology Shenzhen China Mechanisms and Robotics Centre for Robotics Research King's College London UK

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

Traditional quadruped robots usually have rigid and fixed torso, which limits their mobility and flexibility. Robots with movable waist can improve the flexibility and environmental adaptability of robots. In this paper, a novel bionic crawling robot with movable waist is proposed. The movable waist innovatively adopts an anti-parallelogram mechanism. At the same time, the waist adopts a double-layer structure design to increase the stability and bearing capacity of the robot. The kinematics model of the robot is derived based on the D-H parameter method. Bas ed on the Monte Carlo method, the toe workspace of the leg is obtained in Matlab software. The results show that due to the torsion of the movable waist, the toe workspace is significantly expanded, and the robot can achieve faster and smoother motion. A prototype was made based on 3D printing technology for experimental verification.

关键词： Legged locomotion Monte Carlo methods Robot kinematics Prototypes Three-dimensional printing Stability analysis Software

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Vision-Based Tactile Intelligence with Soft Robotic Metamaterial

SSRN

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SSRN 2023年

作者： Wu, Tianyu Dong, Yujian Liu, Xiaobo Han, Xudong Xiao, Yang Wei, Jinqi Wan, Fang Song, Chaoyang Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and Technology China Department of Mechanical and Energy Engineering Southern University of Science and Technology China School of Design Southern University of Science and Technology China

Robotic metamaterials represent an innovative approach to creating synthetic structures that combine desired material characteristics with embodied intelligence, blurring the boundaries between materials and machinery. Inspired by the functional qualities of biological skin, integrating tactile intelligence into these materials has gained significant interest for research and practical applications. This study introduces a Soft Robotic Metamaterial (SRM) design featuring omnidirectional adaptability and superior tactile sensing using a combination of vision-based motion tracking and machine learning. The study compares two sensory integration methods to a state-of-the-art motion tracking system and force/torque sensor baseline: an internal-vision design with high frame rates and an external-vision design offering cost-effectiveness. The results demonstrate the internal-vision SRM design achieving an impressive tactile accuracy of 98.96%, enabling soft and adaptive tactile interactions, especially beneficial for dexterous robotic grasping. The external-vision design offers similar performance at a reduced cost and can be adapted for portability, enhancing material science education and robotic learning. This research significantly advances tactile sensing using vision-based motion tracking in soft robotic metamaterials, and the open-source availability on GitHub fosters collaboration and further exploration of this innovative technology (https://***/bionicdl-sustech/SoftRoboticTongs). © 2023, The Authors. All rights reserved.

关键词： Machine learning

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HITTSFL: Design of a Cost-Effective HIS-Insensitive TNU-Tolerant and SET-Filterable Latch for Safety-Critical Applications

HITTSFL: Design of a Cost-Effective HIS-Insensitive TNU-Tole...

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Design Automation Conference

作者： Aibin Yan Xiangfeng Feng Xiaohu Zhao Hang Zhou Jie Cui Zuobin Ying Patrick Girard Xiaoqing Wen Anhui Engineering Laboratory of IoT Security Technologies / School of Computer Science and Technology Anhui University Hefei China Laboratory of Informatics Robotics and Microelectronics of Montpellier University of Montpellier / CNRS Montpellier France Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan

ISBN: (数字)9781728110851

ISBN: (纸本)9781728158020

This paper proposes a cost-effective, high-impedance-state (HIS)-insensitive, triple-node-upset (TNU)-tolerant and single-event-transient (SET)-filterable latch, namely HITTSFL, to ensure high reliability with low-cost. The latch mainly comprises an output-level SET-filterable Schmitt-trigger and three inverters that make the values stored in three parallel single-node-upset (SNU)-recoverable dual-interlocked-storage-cells (DICEs) converge at a common node to tolerate any possible TNU. The latch does not use C-elements to be insensitive to the HIS. Simulation results demonstrate the TNU-tolerability and SET-filterability of the proposed HITTSFL latch. Moreover, due to the use of clock-gating technologies and fewer transistors, the proposed latch can reduce delay, power, and area by 76.65%, 6.16%, and 28.55%, respectively, compared with the state-of-the-art TNU hardened latch (TNUHL) that cannot filter SETs.

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NANOROBOTIC MANIPULATION OF CARBON NANOTUBES INSIDE A TRANSIMISSION ELECTRON MICROSCOPE

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IFAC Proceedings Volumes 2006年第16期39卷 114-119页

作者： Lixin Dong Bradley J. Nelson Xinyong Tao Li Zhang Xiaobin Zhang Dominic R. Frutiger Arunkumar Subramanian Institute of Robotics and Intelligent Systems ETH Zurich 8092 Zurich Switzerland Dept. of Materials Science and Engineering Zhejiang University Hangzhou 310027 China Laboratory for Micro- and Nanotechnology Paul Scherrer Institute CH-5232 Villigen-PSI Switzerland

Basic processes for nanorobotic manipulation of carbon nanotubes (CNTs) inside a transmission electron microscope are investigated experimentally. These processes are fundamental for the characterization of nanoscale materials, for the structuring of nanosized building blocks, and for the prototyping of nanoelectromechanical systems. Multi-walled CNTs, bamboo-structured CNTs, Cutipped CNTs, and quantum dots attached to CNTs have been used as test structures for manipulation.

关键词： nanorobotic manipulation transmission electron microscope carbon nanotube property characterization NEMS

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Research on the method of path planning for slag-removing on the surface of zinc pot

Research on the method of path planning for slag-removing on...

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第33届中国控制与决策会议

作者： Kebo LI Ling XIONG Zhenzhou ZHANG Gang CHEN Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Key Laboratory of Metallurgical Equipment and Control Technology Wuhan University of Science and Technology

During the production process of cold-rolled hot-dip galvanizing,the slag on the surface of the zinc pot will affect the quality of the *** zinc slag is mostly collected manually or by robots at *** effect of manual salvage is unstable and the operation is *** robot cannot identify the location of the zinc slag and can only salvage it according to a fixed rule,resulting in low *** response to the above problems,a zinc pot slag path planning method based on the greedy algorithm is proposed in this *** zinc pot area is divided,the image processing method is used to identify and locate the zinc slag to be *** the priority of the zinc pot,the obstacle avoidance problem and the restriction of the weight limit of the slag-removing tool are proposed in combination with the process *** three salvage strategies based on the greedy algorithm,the shortest distance,the maximum weight,and the minimum weight are proposed *** results show that the greedy algorithm strategy based on the shortest distance performs best,consumes the least energy,and the algorithm runs for a shorter *** can significantly improve the efficiency of zinc pot slag removal,realize intelligent control of slag removal technology,and can be applied to the actual production of zinc pot slag removal.

关键词： Slag from zinc pot Intelligent control Greedy algorithm Path planning Shortest distance strategy

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Biomechanical models in the lower-limb exoskeletons development: A review

TechRxiv

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TechRxiv 2023年

作者： Firouzi, Vahid Seyfarth, Andre Song, Seungmoon Von Stryk, Oskar Sharbafi, Maziar Ahmad Lauflabor Locomotion Laboratory Institute of Sport Science TU Darmstadt Germany Simulation Systems Optimization and Robotics Group Department of Computer Science TU Darmstadt Germany Mechanical and Industrial Engineering Northeastern University United States

Lower limb exoskeletons serve multiple purposes, like supporting and augmenting movement. Biomechanical models are practical tools to understand human movement, and motor control. This review explores the applications of biomechanical gait models in the development of lower-limb exoskeletons. Biomechanical models can be broadly categorized as conceptual and detailed models. Biomechanical models can be used for the design, control, and assessment of exoskeletons. Also, these models can be used to estimate unmeasurable or hard-to-measure variables, which is also useful within the aforementioned applications. The analysis of applications and research areas aims to inspire further advancements in this field and contribute to the development of more effective exoskeletons. We highlight validating simulation studies, improving the accuracy and fidelity of biomechanical models, and benefiting from exoskeletons to enhance or validate biomechanical models as future research areas related to biomechanical models. We also emphasize the exploration of model-based design and control approaches for exoskeletons targeting pathological gait, and utilizing biomechanical models for diverse design objectives of exoskeletons. Also, increasing the availability of open-source resources accelerates exoskeleton and biomechanical model advancement. Our review reveals existing needs and cracks new perspectives for the development of more usable and human-compatible exoskeletons based on biomechanical models. © 2023, CC BY.

关键词： Exoskeleton (robotics)

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On Embeddings and Inverse Embeddings of Input Design for Regularized System Identification

arXiv

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arXiv 2022年

作者： Mu, Biqiang Chen, Tianshi Kong, He Jiang, Bo Wang, Lei Wu, Junfeng Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen518172 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Key Laboratory for NSLSCS of Jiangsu Province School of Mathematical Sciences Nanjing Normal University Nanjing China College of Control Science and Engineering Zhejiang University Hangzhou China

Input design is an important problem for system identification and has been well studied for the classical system identification, i.e., the maximum likelihood/prediction error method. For the emerging regularized system identification, the study on input design has just started, and it is often formulated as a non-convex optimization problem that minimizes a scalar measure of the Bayesian mean squared error matrix subject to certain constraints, and the state-of-art method is the so-called quadratic mapping and inverse embedding (QMIE) method, where a time domain inverse embedding (TDIE) is proposed to find the inverse of the quadratic mapping. In this paper, we report some new results on the embeddings/inverse embeddings of the QMIE method. Firstly, we present a general result on the frequency domain inverse embedding (FDIE) that is to find the inverse of the quadratic mapping described by the discrete-time Fourier transform. Then we show the relation between the TDIE and the FDIE from a graph signal processing perspective. Finally, motivated by this perspective, we further propose a graph induced embedding and its inverse, which include the previously introduced embeddings as special cases. This deepens the understanding of input design from a new viewpoint beyond the real domain and the frequency domain viewpoints. Copyright © 2022, The Authors. All rights reserved.

关键词： Embeddings

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Terrain Classification Based on Wheel-terrain Interaction Measurements using Aside-Wheel Camera

Terrain Classification Based on Wheel-terrain Interaction Me...

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IEEE International Conference on robotics and Biomimetics

作者： Feng Xue Longteng Hu Chen Yao Jin Wei Yunzhou Li Peichen Wang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China SUSTech Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China Harbin of Institute of Technology (HIT) Harbin China

The scientific applications over a decade have demonstrated the robust practicality of wheeled rovers, which are capable of undertaking exploration tasks in various unstructured terrains. However, sinkage and slippage are extremely common on sandy terrains. Fortunately, these risks can be mitigated in a timely manner through the perception of terrain types. Thus, terrain classification technology has become a key solution to addressing these issues. In this paper, we propose a new terrain classification pipeline for a rover over sandy terrains. It exploits the aside-wheel sensor suite to measure sinkage, contact angle, slip ratio, and normal force. Due to the strong correlation between contact characteristics and terrain types form our experiments, we can infer terrain types based on wheel-terrain interaction parameters. We train various machine learning models and obtained classification results, which is evaluated using the record dataset form a singlewheel testbed. Through Experimental comparison, most models achieve high accuracy (over 90%), we analyze the reasons behind performance discrepancies among different models and recommend LGBM as the preferred approach. In the end, we transfer the models to use data collected from rover field tests and achieve a higher level of accuracy, which proves the effectiveness of our approach.

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