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Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 146-159页

作者： Yinlong Zhang Wei Liang Mingze Yuan Hongsheng He Jindong Tan Zhibo Pang Key Laboratory of Networked Control Systems Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China School of Computing Wichita State UniversityWichita 67260 USA Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeTN 37996 USA Department of Automation Technology ABB Corporate Research SwedenVasteras 72178Sweden Department of Intelligent Systems Royal Institute of Technology(KTH)Stockholm 11428Sweden

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment ***,traditional calibrations suffer inaccuracy and *** address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying *** our method,the spatial relationship is geometrically correlated between the sensing units and robotic *** decoupled estimations on rotation and translation could reduce the coupled errors during the ***,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and *** calibration has been evaluated on our developed *** the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,*** comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

关键词： Calibration inertial measurement unit(IMU) monocular camera robotic arm spiral moving trajectory

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Flapping-Wing Robot Achieves Multi-Domain Locomotion Using Transformable Wheel Mechanism

Flapping-Wing Robot Achieves Multi-Domain Locomotion Using T...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Chai, Xiangxiao Wang, Shihua Pan, Erzhen Xu, Wenfu Shenzhen518055 China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen518055 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

ISBN: (纸本)9781665481090

The difficulty of moving from aquatic to aerial environment is one of the major challenges limiting the development of trans-medium multi-domain locomotion vehicles. In this paper, the concept of the transformable wheel, a feature commonly found in autonomous land vehicles (AL V s), is introduced into the design. Additionally, a flapping-wing robot equipped with multi-domain locomotion capability, which can not only realize aerial flight and surface navigation on water, but also ascend from water to land for subsequent takeoff is presented. The paper first introduces the system design of the robot and proposes the corresponding multi-domain locomotion strategy. Subsequently, the design of the transformable wheel mechanism is described in detail and the force analysis for the water-exit is conducted. The feasibility of the proposed strategy is experimentally validated, confirming the prototype's multi-domain locomotion performance finally. This research explores the feasibility of introducing the transformable wheel mechanism into trans-medium multi-domain vehicle platforms and provides a design example. © 2024 IEEE.

关键词： Machine design

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A Novel Serial-Parallel Hybrid Robot for Rehabilitation Training of Gait and Balance 9

A Novel Serial-Parallel Hybrid Robot for Rehabilitation Trai...

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9th International Conference on Electrical Engineering, Control and robotics, EECR 2023

作者： Shi, Mingsong Hao, Liziyi Zhou, Zhaocheng Liu, Sihui Han, Jianda Yu, Ningbo Nankai University Tianjin Key Laboratory of Intelligent Robotics College of Artificial Intelligence Tianjin300350 China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Guangdong Shenzhen518083 China

ISBN: (纸本)9781665491204

Robot-assisted rehabilitation training for lowerlimb function recovery has gained increasing acceptability, but simultaneous training of gait and balance has not been well explored. In this paper, we propose a novel 5-DOF serial-parallel hybrid end-effort robot to provide gait training, balance training, as well as gait and balance training. Each side of the robot is composed of a 2-DOF gait generator and a 3-DOF parallel balance module. The gait generator takes the H-Bot mechanism, which distributes the heavy load of the patient to the two motors during walking, which are connected in serial. For the balance module, its virtual rotation center of the footplate is designed to be aligned with the ankle joint, enabling natural balance adjustment and training. Further, two displacement sensors and an inclinometer are employed to measure the pose, and closed-loop control of the 2-DOF position and 3-DOF orientation of the robot end-effector is realized. The robotic system has been built up, and achieved good performance on position and pose tracking, promising an effective rehabilitation platform for independent and simultaneous training of gait and balance. © 2023 IEEE.

关键词： End effectors

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Instruction Pre-Training: Language Models are Supervised Multitask Learners

Instruction Pre-Training: Language Models are Supervised Mul...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Cheng, Daixuan Gu, Yuxian Huang, Shaohan Bi, Junyu Huang, Minlie Wei, Furu Microsoft Research United States The CoAI Group DCST Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University China

ISBN: (纸本)9798891761643

Unsupervised multitask pre-training has been the critical method behind the recent success of language models (LMs). However, supervised multitask learning still holds significant promise, as scaling it in the post-training stage trends towards better generalization. In this paper, we explore supervised multitask pretraining by proposing Instruction Pre-Training, a framework that scalably augments massive raw corpora with instruction-response pairs to pre-train LMs. The instruction-response pairs are generated by an efficient instruction synthesizer built on open-source models. In our experiments, we synthesize 200M instruction-response pairs covering 40+ task categories to verify the effectiveness of Instruction Pre-Training. In pre-training from scratch, Instruction Pre-Training not only consistently enhances pre-trained base models but also benefits more from further instruction tuning. In continual pre-training, Instruction Pre-Training enables Llama3-8B to be comparable to or even outperform Llama3-70B. Our model, code, and data are available at https://***/microsoft/LMOps. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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Editorial

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Computational Intelligence 2023年第4期39卷 530-531页

作者： Er, Meng Joo Ju, Zhaojie Ferrein, Alexander Changjiang Scholar Distinguished Director of Institute of Artificial Intelligence and Marine Robotics College of Marine Electrical Engineering Dalian Maritime University Dalian China Reader in Machine Learning and Robotics School of Computing University of Portsmouth Portsmouth United Kingdom Department of Electrical Engineering and Information Technology Mobile Autonomous Systems & Cognitive Robotics Institute Robotics and Foundations of Computer Science FH Aachen - University of Applied Sciences Aachen Germany

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Design and Experimental Evaluation of WLR-III

Design and Experimental Evaluation of WLR-III

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Li, Xu Fu, Yili Zhejiang University State Key Laboratory of Robotics and System Harbin Institute of Technology State Key Laboratory of Fluid Power and Mechatronic Systems China Harbin Institute of Technology Intelligent Robot Research Center Zhejiang Laboratory State Key Laboratory of Robotics and System Heilongjiang Province Harbin150001 China

ISBN: (纸本)9798350325706

This paper introduces the design and experimental evaluation of WLR-III, which stands for the third-generation hydraulic wheel-legged robot. WLR-III is expected to be applied to disaster scenarios where the mobility, adaptability and manipulation capability are required. Based on the development of the previous two generations of wheel-legged robots, this work continuously optimizes the design to achieve higher mobility and stronger adaptability by reducing weight & inertia. The hydraulic power transmission system adopts a hose-less design method to ensure the robustness of the system. What's more prominent is that the successful development of hydraulic power unit (HPU) enables WLR-III to realize hydraulic power autonomy. In addition, to accomplish all kinds of operational tasks in the rescue scene, the electro-hydraulic hybrid drives anthropomorphic arms with heavy load grippers were developed. Finally, the effectiveness and reliability of design optimization have been evaluated through a series of experiments, including grassland movement, load bearing, obstacle-stepping and tool-operating. To the authors' best knowledge, this is the first time that a hydraulic powered autonomous wheel-legged humanoid robot with the ability to operate simple tools has been developed. © 2023 IEEE.

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Polarization-controlled dual resonant lattice Kerker effects

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Nano Research 2023年第2期16卷 3195-3200页

作者： Lei Xiong Xueqian Zhao Xiang Du Shuai Chen Yuanfu Lu Hongwei Ding Guangyuan Li School of Information Science and Engineering Yunnan UniversityKunming 650500China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Computer Electronic and InformationGuangxi UniversityNanning 530004China College of Physics and Electronic Technology Anhui Normal UniversityWuhu 241000China Tianjin H-Chip Technology Group Corporation Tianjin 300467China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen 518055China

The generalized Kerker effects have attracted increasing interests in recent years due to their abilities to manipulate the far-field properties of ***,the dual-polarized generalized Kerker effect enabling different tailoring of orthogonally-polarized electromagnetic waves has not yet been ***,we demonstrate polarization-controlled dual resonant lattice Kerker effects in periodic silicon *** varying the incident angle,the electric dipole and magnetic dipole surface lattice resonances can spectrally overlap,causing zero reflectance and unitary transmittance,i.e.,the resonant lattice Kerker *** incident angle for achieving this effect can be tuned differently for s-and p-polarizations over large regions by varying the nanodisk size or the lattice *** proposed dual-polarized resonant lattice Kerker effects open up avenues for polarization-controlled manipulation of the phase and wavefront of light with metasurfaces.

关键词： Kerker effect surface lattice resonances dual-polarized silicon metasurface

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Lidar-Inertial and Downward Vision Based Mobile Robot SLAM in Digital Workshops 13

Lidar-Inertial and Downward Vision Based Mobile Robot SLAM i...

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13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： Zhang, Yanchao Geng, Hao Liu, Bin Zhang, Yinlong Yuan, Xudong Zhang, Sichao School of Information Science and Engineering Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350361674

In order to solve the problems of long-term cumulative error and the absence of absolute pose in the existing Lidar-Inertial Measurement Unit (IMU) fusion methods for Automated Guided Vehicle (AGV) Simultaneous Localization and Mapping (SLAM), we propose a new SLAM method for mobile robot, integrating Lidar, IMU, and a downward vision camera. Firstly, we tightly couple Lidar-IMU and downward vision camera using a multimodal fusion framework. Downward visual measurements are integrated as QR factors into the factor graph, providing absolute pose information to correct cumulative error in the Lidar-IMU system and enable the joint pose estimation of the AGV. Secondly, an enhanced Iterative Closest Point (ICP) point cloud matching algorithm has been developed to correct the incorrect pose. This approach achieves Scan-to-Map alignment by employing a coarse-to-fine matching strategy, thereby enhancing the accuracy of point cloud alignment. Finally, the extended Kalman filter is used to optimize the Lidar pose drift, as well as the Lidar mapping effectively by using the Lidar-IMU as the measurements and the downward visual measurements as the updates. The algorithm has been extensively evaluated on the developed AGV experimental platform. The experimental results show that the position error is less than 0.02 meters and the orientation error is less than 1°, which solves the problems of long-term error accumulation and the lack of absolute pose information for AGV navigation. © 2024 IEEE.

关键词： Extended Kalman filters

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Learning Hierarchical Robot Skills Represented by Behavior Trees from Natural Language 29th

Learning Hierarchical Robot Skills Represented by Behavior ...

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29th International Conference on Cooperative information systems, CoopIS 2023

作者： Wang, Kaiyi Zhao, Yongjia Dai, Shuling Yang, Minghao He, Yichen Zhang, Ning State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Jiangxi Research Institute Beihang University Jiangxi China Institute of Automation Chinese Academy of Sciences Beijing China Institute of Intelligent Information Processing Beihang University Beijing China

ISBN: (纸本)9783031468452

Learning from natural language is a programming-free and user friendly teaching method that allows users without programming knowledge or demonstration capabilities to instruct robots, which has great value in industry and daily life. The manipulation skills of robots are often hierarchical skills composed of low-level primitive skills, so they can be conveniently represented by behavior trees (BTs). Based on this idea, we propose NL2BT, a framework for generating behavior trees from natural language and controlling robots to complete hierarchical tasks in real time. The framework consists of two language processing stages, an initial behavior tree library composed of primitive skill subtrees, and a BT-Generation algorithm. To validate the effectiveness of NL2BT, we use it to build a Chinese natural language system for instructing robots in performing 3C assembly tasks, which is a significant application of Industry 4.0. We also discuss the positive impact of real-time teaching, visual student models, and the synonymous skill module in the framework. In addition to the demonstrated application, NL2BT can be easily migrated to other languages and hierarchical task learning scenarios. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Robot programming

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Big Data Processing for Bulgarian Healthcare - Smart Cards and Some Simulating Decisions 8

Big Data Processing for Bulgarian Healthcare - Smart Cards a...

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8th International Conference on Big Data, Knowledge and Control systems Engineering, BdKCSE 2023

作者： Boneva, Ani Ivanova, Veronika Vasilev, Plamen Ivanov, Stoyan Ivanova, Tsvetelina Institute of Information and Communication Technologies Bulgarian Academy of Sciences Department of Communication Systems and Services Sofia Bulgaria Institute of Robotics Bulgaria Academy of Sciences Department of Robotized and Mechatronics Intelligent Systems Sofia Bulgaria University of Chemical Technologies and Metallurgy Department of Industrial Automation Sofia Bulgaria

ISBN: (纸本)9798350313246

This publication presents a review of the application of large databases (Big Data) in medicine. The aim of the work is to provide some positive guidelines for the optimization of health care and improvement of patient care in Bulgaria. Therefore, the article discusses designed applications that can find their place in various fields of medicine. Our proposed optimization is the introduction of electronic chip cards. The development assumes that each patient will be provided with a processor card carrying information about basic data related to the condition and its personalization and possible access to this data when necessary. Thus, the proposed solution provides an opportunity to upgrade (for the future) and build an information system with a connection to the health fund. In addition, an early-stage project is described to integrate data from personal portable devices with the electronic health record, thereby providing information to medical personnel about the individual's health status. Portable personal devices and other non-medical equipment generate a huge, almost continuous flow of data that can be useful in making decisions regarding the treatment of patients with various health conditions. The applications described are a continuation of the team's previous developments. © 2023 IEEE.

关键词： intelligent systems

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