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arXiv 2023年

作者： Tong, Xin Cheng, Shing Shin Department of Mechanical and Automation Engineering CUHK T Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Department of Mechanical and Automation Engineering CUHK T Stone Robotics Institute Shun Hing Institute of Advanced Engineering Multi-Scale Medical Robotics Center The Chinese University of Hong Kong Hong Kong

Existing approaches to robust global asymptotic stabilization of a pair of antipodal points on unit n-sphere Sn typically involve the non-centrally synergistic hybrid controllers for attitude tracking on unit quaternion space. However, when switching faults occur due to parameter errors, the non-centrally synergistic property can lead to the unwinding problem or in some cases, destabilize the desired set. In this work, a hybrid controller is first proposed based on a novel centrally synergistic family of potential functions on Sn, which is generated from a basic potential function through angular warping. The synergistic parameter can be explicitly expressed if the warping angle has a positive lower bound at the undesired critical points of the family. Next, the proposed approach induces a new quaternion-based controller for global attitude tracking. It has three advantageous features over existing synergistic designs: 1) it is consistent, i.e., free from the ambiguity of unit quaternion representation;2) it is switching-fault-tolerant, i.e., the desired closed-loop equilibria remain asymptotically stable even when the switching mechanism does not work;3) it relaxes the assumption on the parameter of the basic potential function in literature. Comprehensive simulation confirms the high robustness of the proposed centrally synergistic approach compared with existing non-centrally synergistic approaches. © 2023, CC BY-NC-ND.

关键词： Hybrid systems

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Design and path planning for a Worm-Snake-Inspired Metameric(WSIM) Robot

Design and path planning for a Worm-Snake-Inspired Metameric...

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IEEE International Conference on robotics and Biomimetics

作者： Zhihai Bi Jian Xu Hongbin Fang Institute of AI and Robotics Fudan University Shanghai China MOE Engineering Research Center of AI & Robotics and Shanghai Engineering Research Center of AI & Robotics Fudan University Shanghai China

ISBN: (纸本)9781665481106

Compared with the traditional wheeled and legged robots, limbless metameric robots such as snake-like and worm-like robots are more efficient in moving in an unstructured environment, which can better satisfy the requirements of special tasks such as earthquake rescue and pipeline inspection. To this end, this paper presents a renewed sense of design and the path-planning algorithm for the WSIM robot. Then, a robot prototype is established and analyzed. Experiments reveal that the robot has the ability of multi-modal locomotion, which is suitable for both open and narrow terrains. In addition, a collision-free path planning method considering kinematic constraints is proposed based on the trajectory library, bounding box, and discrete A* algorithm. The simulation results show that the algorithm is robust and well fits the WSIM robot with multi-modal locomotion capability.

关键词： Legged locomotion Simulation Pipelines Prototypes Kinematics Inspection Robot sensing systems

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A Novel Dense Object Detector with Scale Balanced Sample Assignment and Refinement

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Dong, Jinpeng Yao, Dingyi Hu, Yufeng Zhou, Sanping Zheng, Nanning Xi’an Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an710049 China Xi’an Jiaotong University Shaanxi Xi’an710049 China

Scale variation of objects remains one of the crucial challenges in object detection. Currently, conventional dense detectors with fixed receptive fields and label weights are not conducive to the detection of multi-scale objects. However, the design limitations of unbalanced label weights and fixed refinement for multi-scale objects and multi-tasks in these studies make it difficult to achieve better detection performance. In this paper, we propose a novel dense detector named Balanced FCOS which consists of two components: Balanced Label Assignment (BLA) and Flexible Shape-based Refinement (FSR). The BLA implements scale-balanced sample assignment by introducing reweighting factors consisting of localization and classification scores into the label assignment. Low-quality but high-weight samples can be weakened by the BLA. Furthermore, we design a cross-reweighting mechanism in the BLA to ensure score consistency between classification and localization. The FSR implements scale-balanced sample refinement by learning flexible sample points’ offsets for multi-scale objects and multi-tasks based on objects’ coarse features to get more discriminative features with appropriate receptive field. In addition, better features obtained by FSR are beneficial to get better classification and localization scores, which can be used by BLA to produce accurate label weights. Only equipped with the BLA, we can achieve 41.7/46.6 AP under R50/R101-FCOS without any additional parameters. When combining the BLA with the FSR, our Balanced FCOS achieves SOTA results among dense detectors on the COCO test-dev set. Experiments conducted on other heads (T-Head, DyHead), detectors (DINO), and datasets (AI-TOD) further demonstrate the effectiveness of our method. (Figure presented) © 1991-2012 IEEE.

关键词： Object detection

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Development of an Electronically Controlled Pneumatic Knee Prosthesis System for Assisting Gait in Lower-limb Amputees

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Journal of institute of Control, robotics and Systems 2025年第5期31卷 536-545页

作者： Kim, Seung-Gi Park, Jin-Kook Shin, Hyun-Jun Eom, Su-Hong Kim, Kyoung-Ho Park, Se-Hoon Korea Orthopedics and Rehabilitation Engineering Center Korea Workers' Compensation and Welfare Service Korea Republic of Department of Electrical Engineering Tech University of Korea Korea Republic of Korea Institute of Robotics and Technology Convergence Korea Republic of

This study introduces an electronically controlled pneumatic knee (ECPK) prosthesis designed to enhance gait adaptability and stability in transfemoral amputees. While pneumatic prostheses are lightweight and cost-efficient, they often lack responsiveness and stability. Therefore, a 4-bar linkage mechanism with a pneumatic cylinder is implemented, along with a motor-driven control algorithm using a unipolar Hall sensor to adjust damping based on real-time gait phase detection. A dedicated PC application is also developed to monitor gait parameters and configure control settings. Gait experiments with a transfemoral amputee demonstrate that an ECPK prothesis improves step length symmetry, dynamic stability, and responsiveness over fixed-nozzle and conventional pneumatic prostheses. These findings suggest that the ECPK prosthesis effectively bridges the gap between simple mechanical design and adaptive performance, providing a practical and scalable solution for improving prosthetic gait support. © ICROS 2025.

关键词： Knee prostheses

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A Review on On Device Privacy and Machine Learning Training 2

A Review on On Device Privacy and Machine Learning Training

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2nd IEEE International Conference on Artificial Intelligence in Everything, AIE 2022

作者： Tonga, Paul Audu Ameen, Zubaida Said Mubarak, Auwalu Saleh Al-Turjman, Fadi Ai and Robotics Institute Near East University Research Center for Ai and IoT Artificial Intelligence Dept Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Cyprus

ISBN: (数字)9781665474009

ISBN: (纸本)9781665474009

On device machine learning has in recent times attracted growing attention and applications, ranging from advanced OCR and handwriting recognition, smart sleep tracking in Apple iOS, mobile virtual assistants and Image recognition, text translation in android;and more. As a result, there is increasing demand for user privacy and security in machine learning applications. Federated Learning (FL), a new method, allows users to cooperatively train a global model while keeping the data local, thereby resolving the issue of data privacy protection through the encryption mechanism. The server aggregates models until convergence while the clients train their local models. In this procedure, the server employs a reward system to persuade users to provide huge amounts of high-quality data in order to enhance the overall model. This paper explores a few FL techniques that can be applied alongside on-device learning, in order to achieve better privacy and security. © 2022 IEEE.

关键词： Internet of things

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Cable-Integrated Single-Axis Load Cell for Tendon-Driven Robotic Actuation Enabled by Thin-Film Soft Sensor

Cable-Integrated Single-Axis Load Cell for Tendon-Driven Rob...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Jiyeon Cho Taejun Park Simon Kim Yong-Lae Park Department of Mechanical Engineering Institute of Advanced Machines and Design Institute of Engineering Research Seoul National University Seoul Korea Soft Robotics and Bionics Lab. Seoul National University Seoul Korea

Cable-driven force transmission is one of the most widely used actuation mechanisms in robotics, finding applications in robotic arms, grippers, and wearable robots. However, measuring cable tension directly is challenging due to limited space and difficulties in attaching sensors to flexible cables. In this paper, we propose a single-axis load cell designed for direct integration into a high-strength woven cable, enabling tension measurement. A small portion of the cable becomes slightly stretchable by infusing an uncured polymer into its weaving pattern, and a liquid-metal thin-film soft sensor is affixed externally. As the cable experiences axial strain, the thin-film soft sensor stretches and changes its electrical resistance, providing real-time tension information. To mitigate the hysteresis and the nonlinearity caused by the viscoelastic effect of the cable and tendon materials, a metal spring casing surrounds the sensor, making the behavior of the sensor governed by that of the spring. The proposed sensor is experimentally characterized, and the result shows a linearity in the range of 5 N to 100 N with negligible hysteresis. It is tested with a twisted-string actuator to control the axial force generated by the actuator through a closed-loop control as an application.

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Design and Development of the Dual-Arm Robot DARO

Design and Development of the Dual-Arm Robot DARO

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WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Yun Liu Qiulang Huang Pu Zhang Mindong Yan Dingkun Liang Lingyu Kong Xin Wang Anhuan Xie Jason Gu Shiqiang Zhu Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Electrical and Computer Engineering Dalhousie University Halifax NS Canada

This paper presents the design and development of a humanoid dual-arm robot called DARO, along with its improved version, DARO-N. DARO and DARO-N consist of two arms and humanoid hands, each with 6/7 degrees of freedom for the arms and 7 active degrees of freedom for the hands. Modular commercial actuators are employed as the driving joints of the arms, allowing for reduced development time and cost. The design principles of modularity, simplicity, lightweight construction, human likeness, information perception capability, and scalability are incorporated into the design. Furthermore, this work establishes a control framework for the humanoid dual-arm robot and conducts simulations and multiple physical experiments to validate the performance of the robots.

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Two-Photon Image-Guided Automated 3D Locating of Micropipette Tip

Two-Photon Image-Guided Automated 3D Locating of Micropipett...

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第43届中国控制会议

作者： Zizhen Li Jie Li Qili Zhao Xin Zhao Mingzhu Sun National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Tianjin Key Laboratory of Intelligent Robotics (tikLIR) Institute of Robotics and Automatic Information System (IRAIS) Nankai University Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

The 21st century has been universally recognized by the scientific community as the era of neuroscience, with the patch clamp technique serving as a key to unraveling the intricate mysteries of brain science. Due to its advantages such as reduced sample damage and enhanced penetration capability, the application of two-photon microscope in deep imaging of live animals has become prevalent, making it a preferred choice over confocal microscope. At present, there exist a few near complete automation techniques of image-guided patching in vivo, which typically start from the micropipette tip appearing in the imaging field of view. The operational workflow for the step involving the installation of the micropipette until the micropipette tip becomes visible within the field of view has regrettably not been provided. However, it is crucial information that is of utmost importance to experimental personnel. In this paper, we present a comprehensive workflow for 3D locating of micropipette tip in a self-built two-photon microscope tailored for patch clamp experiments. Moreover, by fully incorporating the distinctive features of two-photon imaging, the study applies statistical methods to achieve automated execution of the corresponding workflow. The experimental results indicate that the process of micropipette tip locating takes an average of 58.4 ***, the method is not sensitive to parameter selection, allowing experimenters to obtain suitable parameters for different systems through simple testing. The automated 3D micropipette tip locating method proposed in this paper, with its versatility, holds great potential for seamless integration into commercial two-photon microscope systems. It significantly contributes to reducing the work burden on experimenters and minimizing the time required for experimental preparation.

关键词： 3D micropipette tip locating two-photon microscope automated method

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HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene

arXiv

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arXiv 2024年

作者： Guo, Ziang Perminov, Stepan Konenkov, Mikhail Tsetserukou, Dzmitry Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Moscow Russia LLC IntegraNT Moscow Russia

Many established vision perception systems for autonomous driving scenarios ignore the influence of light conditions, one of the key elements for driving safety. To address this problem, we present HawkDrive, a novel perception system with hardware and software solutions. Hardware that utilizes stereo vision perception, which has been demonstrated to be a more reliable way of estimating depth information than monocular vision, is partnered with the edge computing device Nvidia Jetson Xavier AGX. Our software for low light enhancement, depth estimation, and semantic segmentation tasks, is a transformer-based neural network. Our software stack, which enables fast inference and noise reduction, is packaged into system modules in Robot Operating System 2 (ROS2). Our experimental results have shown that the proposed end-to-end system is effective in improving the depth estimation and semantic segmentation performance. Our dataset and codes will be released at https://***/ZionGo6/HawkDrive. © 2024, CC BY-NC-ND.

关键词： Robot Operating System

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HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene

HawkDrive: A Transformer-driven Visual Perception System for...

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IEEE Symposium on Intelligent Vehicle

作者： Ziang Guo Stepan Perminov Mikhail Konenkov Dzmitry Tsetserukou Intelligent Space Robotics Laboratory Center for Digital Engineering Skolkovo Institute of Science and Technology Moscow Russia LLC IntegraNT Moscow Russia

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

关键词： Semantic segmentation Estimation Cameras Transformers Hardware Software Stereo vision

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