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Teleoperation of Multi-functional Neurosurgical Tool∗ 5

Teleoperation of Multi-functional Neurosurgical Tool∗

引用

5th World Robot Conference Symposium on Advanced robotics and automation, WRC SARA 2023

作者： Ma, Xudong Yao, Lechen Chen, Anqi Wang, Junchen Li, Changsheng Liu, Wenyong Hu, Yida David Su, Bai-Quan Beijing University of Posts and Tele-communications Medical Robotics Laboratory School of Automation Beijing100876 China Affiliated High School of Peking University Beijing100190 China Beihang University School of Mechanical Engineering and Automation Beijing100083 China School of Mechatronical Engineering Beijing Institute of Technology Beijing100081 China Beihang University Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beijing100083 China Brigham and Women's Hospital Harvard Medical School BostonMA02115 United States

ISBN: (纸本)9798350307320

Fluid removal and electrotome coagulation are routine procedures in neurosurgery operations, and the doctor's remote control can reduce physical fatigue. In this paper, an integrated multi-functional surgical tool which can realize electrocoagulation and liquid aspiration is designed. At the same time, the multi-functional integrated surgical device is combined with the remote operation method to realize the remote operation of the instrument. This multifunctional instrument includes CCD-imaging, suction and electrical coagulation. The system can complete the remote operation function of the special design tool, and can isolate the doctor from the operation. The teleoperation of this instrument is integrated with the teleoperation of other functional instruments to realize the teleoperation of the complete surgical process. © 2023 IEEE.

关键词： Remote control

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CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face Anti-Spoofing

CPL-CLIP: Compound Prompt Learning for Flexible-Modal Face A...

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Ying Zhang Xiangyu Zhu Ajian Liu Xun Lin Jun Wan Jing Zhang Zhen Lei State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences School of Computer Science and Engineering Beihang University School of Computer Science and Engineering Macau University of Science and Technology Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Chinese Academy of Sciences

ISBN: (数字)9798350364132

ISBN: (纸本)9798350364149

Face anti-spoofing (FAS) is pivotal in safeguarding the integrity of face recognition systems. Flexible-modal FAS utilizes multi-modal data and trains a unified model adaptable to any single-modal testing scenario. This innovation addresses the shortcomings of conventional multi-modal FAS approaches, which typically demand separate model training and deployment for each modality. However, existing flexible-modal FAS approaches activate specific network branches based on the modality of the tested sample. This not only increases the model’s parameters but also necessitates the provision of the image’s modality for testing, thereby constraining deployment flexibility. To address the issue, we present Compound Prompt Learning CLIP (CPL-CLIP), a novel method for flexible-modal FAS. This approach capitalizes on a learned textual prompt that is nearly independent of modality, thus bolstering class-based classification across arbitrary modalities. Specifically, our CPL-CLIP introduces a Dual-Branch Prompt (DBP), consisting of class and modal prompts that describe and guide classification, where each prompt is composed of learnable vectors and fixed templates. To further render the class prompt as modality-agnostic as possible, a Cosine Similarity Loss (CSL) is proposed to facilitate the maximal separation of the class prompt from the modality prompt. With only the class prompt utilized during testing, CPL-CLIP enables deployment in diverse modal testing scenarios without the necessity of the test image’s modality to be known. Extensive experiments demonstrate CPL-CLIP’s superiority over existing methods on several flexible-modal FAS benchmarks.

关键词： Training Adaptation models Technological innovation Accuracy Face recognition Benchmark testing Vectors Robustness Data models Compounds

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Web Based Lidar Point Cloud Visualization and Teleoperation Tool for Robots

Web Based Lidar Point Cloud Visualization and Teleoperation ...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Suraj Nukala Midori Sugaya Seenu Nagarajan Department of Mechatronics Engineering Hindustan Institute of Technology and Science Chennai Tamil Nadu India Department of Computer Science Shibaura Institute of Technology Tokyo Japan Department of Mechatronics Engineering Centre for Automation and Robotics (ANRO) Hindustan Institute of Technology and Science Chennai 603103 Tamil Nadu India

This paper presents the development of a teleoperation system designed for remote control of a ROS robot over the internet. While existing visualization tools like rvis are limited to the host system or local area network, this system aims to overcome those constraints. The system's primary objectives are remote motor control and lidar data visualization using point cloud and camera data, and it is compatible with any ROS system, tested with ROS2 *** system meets the following requirements:*** ability to work over the *** ability to visualize lidar and camera *** ability to control *** achieve this, the system relies heavily on ROSBridge, which is a ROS node that exposes ROS communication channels such as topics, services, and activities out to the internet using websockets. This enables any client to subscribe and publish data to and from the ROS communication *** user interface of envious incorporates various interactive elements, including the camera feed, motor controllers, and lidar data visualization. These components are implemented using roslibjs, react, and react three fiber, which leverages webgl and threejs libraries to create an abstraction layer for seamless integration with the web *** leveraging ROSBridge and modern web technologies, the proposed system offers the ability to control motors and visualize lidar and camera data remotely over the internet. It provides a user-friendly interface for interacting with the ROS system, facilitating teleoperation of robots from any location with an internet connection. This system expands the capabilities of ROS beyond local networks, opening up new possibilities for remote robotics applications and *** the capabilities of this system would opens up a world of exciting applications, one of which is a swarm mapping system that takes leverage of multiple interconnected robots to collaboratively map and explore an area

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MTPA-based Haptic Feedback Controller for Master Manipulator in Minimally Invasive Surgery

MTPA-based Haptic Feedback Controller for Master Manipulator...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhao, Wenda Chen, Jian Hong, Yilun Liu, Hongbin School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Hong Kong School of Biomedical Engineering and Imaging Sciences King's College London LondonSE1 7EU United Kingdom

ISBN: (纸本)9781665481090

Haptic feedback is critical for teleoperation in surgical robots, particularly in Natural Orifice Transluminal Endoscopic Surgery (NOTES). This paper introduces a haptic controller designed to enhance force generation efficiency and resolution, surpassing traditional motor control frameworks. We propose a Maximum Torque Per Ampere (MTPA)-based Field-Oriented Control (FoC) strategy for haptic kinesthetic feedback controller, optimizing the performance of a master manipulator's joint with a brushless DC (BLDC) motor under stalled and ultra-slow conditions. This approach enables a master manipulator with three degrees of freedom (DoF) for force feedback. Its effectiveness is validated through simulator and surgical trials, demonstrating improved haptic feedback in surgical applications. © 2024 IEEE.

关键词： Brushless DC motors

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BLIP-Adapter: Bridging Vision-Language Models with Adapters for Generalizable Face Anti-spoofing 18

BLIP-Adapter: Bridging Vision-Language Models with Adapters ...

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18th IEEE International Joint Conference on Biometrics, IJCB 2024

作者： Zhang, Bin Zhu, Xiangyu Gao, Li Zhang, Xiaoyu Lei, Zhen Chinese Academy of Sciences Institute of Information Engineering China University of Chinese Academy of Sciences School of Cyber Security China China Mobile Financial Technology Co. Ltd. China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation China University of Chinese Academy of Sciences School of Artificial Intelligence China Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Hong Kong

ISBN: (纸本)9798350364132

Face anti-spoofing is essential for ensuring the security of facial recognition systems against spoofing attacks. Recent methods have transferred Vision-Language models to face anti-spoofing (e.g., FLIP and CLIPC8), demonstrating that learning perception from supervision in natural language can enhance the model's detection performance. However, such methods exhibit limited depth in the interaction between images and texts, resulting in poor performance on fine-grained understanding tasks such as face anti-spoofing. Besides, the lack of diversity in image-text pairs for face anti-spoofing further hinders such methods from playing their best. To address these issues, we propose a novel fine-tuning strategy for Vision-Language models in face anti-spoofing. This strategy introduces the Bootstrapping Language-Image Pre-training model (BLIP), known for its novel interaction mechanisms and superior image-text comprehension, to construct a more generalized feature representation for face anti-spoofing. Furthermore, we propose an Adapter module for the text branch to reduce the negative impact of insufficient data diversity and catastrophic forgetting. Extensive experiments conducted on various cross-domain testing benchmarks demonstrate the significant superiority of our method over the state-of-the-art, highlighting its effectiveness and robustness. © 2024 IEEE.

关键词： Visual languages

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A Novel Interoperability Evaluation Framework for the Warehouse Management System

A Novel Interoperability Evaluation Framework for the Wareho...

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Annual Conference of Industrial Electronics Society

作者： Tijo Thayil Jingbing Zhang Prahlad Vadakkepat Abdullah Al Mamun Krishna Sagar Smart Robotics and Automation Advanced Remanufacturing & Technology Centre (ARTC) Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore Dept. of Electrical and Computer Engineering College of Design and Engineering National University of Singapore Advanced Remanufacturing & Technology Centre (ARTC) Agency for Science Technology and Research (A*STAR) Singapore Republic of Singapore

Warehouse management is a critical element in the supply chain. The rise of e-commerce demands ‘any-mix any-volume’ customized and personalized orders. Due to the variety of products in ‘any-mix any-volume’ scenario the warehouse operations have become complex. The advent of multi-channel commerce has reduced the minimum order quantity (MOQ), claiming frequent changes. The ‘any-mix any-volume’ operations require flexible automation for product storage, retrieval, packing and shipping. Seamless operations of multiple devices are essential for automating flexible warehouses. For effective flexible operations, the Warehouse Management System (WMS) requires controlling the automation devices and associated auxiliary systems. Heterogenous automation devices with distinct communication protocols, data formats and connectivity are challenges for WMS centered control. An interoperable WMS can enable seamless communication and data exchange among devices. In this work, the interoperability of the WMS and various aspects of interoperability of engineering systems are presented. Different WMS system designs are considered and evaluated for the interoperability requirements. A framework for evaluating the interoperability of a WMS is proposed which is validated through experimental trials at an industry grade warehouse.

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Miniature Reconfigurable Modular Soft Robots Using Liquid Crystal Elastomer Actuation

Miniature Reconfigurable Modular Soft Robots Using Liquid Cr...

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

作者： Huayu Zhang Jiajun An Tianle Pan Upinder Kaur Zhijian Wang Xuchen Wang Qiguang He Xin Ma Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong SAR Multiscale Medical Robotics Centre Hong Kong SAR Department of Agricultural and Biological Engineering Purdue University USA Key Laboratory of Aerospace Advanced Materials and Performance Ministry of Education School of Materials Science and Engineering Beihang University China

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

Soft robotics is rapidly evolving, fueled by advancements in controllable materials. Liquid crystal elastomers (LCEs) stand out with their exceptional actuation capabilities, ease of processing, and built-in programmability. However, current LCE robots struggle with limited dexterity and adaptability, hindering their real-world potential. We address this limitation by introducing a novel modular design approach that unlocks the full potential of LCEs. Our miniature, highly deformable soft robot utilizes reconfigurable LCE modules for bending and twisting, enabling enhanced manipulability through serial combinations. Demonstrating its dexterity, the modular robot performs intricate fingertip manipulation, allowing a miniature gripper to rotate a small object. This achievement highlights the reconfigurability and utility of our system, paving the way for more dexterous and versatile LCE-based robots.

关键词： Elastomers Soft robotics Bending Grippers

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Sliding Mode Even-Triggered Tracking Control for Robot Manipulators With State Constrains 48

Sliding Mode Even-Triggered Tracking Control for Robot Manip...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Soni, Sandeep Kumar Kumar, Sunil Wang, Siyuan Sachan, Ankit Boutat, Driss Geha, Daniel University d'Orleans Insa Centre Val de Loire Prisme Ea 4229 Bourges18000 Cedex France Department of Electrical Engineering U.P. Varanasi221005 India Hiroshima University Graduate School of Advanced Science and Engineering Higashi Japan Industrial Automation Robotics 1 Chemin de La Bourellerie Thenioux18100 France

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper presents the sliding mode event-triggered control to solve the trajectory tracking problem of robot manipulator systems under state constraints. Through the design of time-varying control gains, a Lyapunov function ensures the fulfilment of the state constraints despite external disturbances. The designed sliding mode event-triggered control ensures that the sliding variable reaches the vicinity of the sliding surface in the finite-time. Furthermore, the proposed method ensures the uniform ultimate boundedness of the tracking error. There is no accumulation of inter-event time, which provides Zeno-free study. Simulation results of two-link robotic manipulator demonstrate the effectiveness of the proposed theory. © 2022 IEEE.

关键词： Lyapunov functions

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Active Generalized Category Discovery

Active Generalized Category Discovery

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Shijie Ma Fei Zhu Zhun Zhong Xu-Yao Zhang Cheng-Lin Liu MAIS Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China Centre for Artificial Intelligence and Robotics HKISI-CAS China School of Computer Science and Information Engineering Hefei University of Technology China School of Computer Science University of Nottingham Nottingham UK

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Generalized Category Discovery (GCD) is a pragmatic and challenging open-world task, which endeavors to cluster unlabeled samples from both novel and old classes, leveraging some labeled data of old classes. Given that knowledge learned from old classes is not fully transferable to new classes, and that novel categories are fully unlabeled, GCD inherently faces intractable problems, including imbalanced classification performance and inconsistent confidence between old and new classes, especially in the low-labeling regime. Hence, some annotations of new classes are deemed necessary. However, labeling new classes is extremely costly. To address this issue, we take the spirit of active learning and propose a new setting called Active Generalized Category Discovery (AGCD). The goal is to improve the performance of GCD by actively selecting a limited amount of valuable samples for labeling from the oracle. To solve this problem, we devise an adaptive sampling strategy, which jointly considers novelty, informativeness and diversity to adaptively select novel samples with proper uncertainty. However, owing to the varied orderings of label indices caused by the clustering of novel classes, the queried labels are not directly applicable to subsequent training. To overcome this issue, we further propose a stable label mapping algorithm that transforms ground truth labels to the label space of the classifier, thereby ensuring consistent training across different active selection stages. Our method achieves state-of-the-art performance on both generic and fine-grained datasets. Our code is available at https://***/mashijie1028/ActiveGCD

关键词： Training Computer vision Uncertainty Computational modeling Clustering algorithms Transforms Pattern recognition

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Towards Fast Face Image Quality Assessment via Latent Diffusion Model 18th

Towards Fast Face Image Quality Assessment via Latent Diffu...

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18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Yan, Zheyu Zhao, Weisong Zhu, Xiangyu Gao, Li Zhang, Xiao-Yu Lei, Zhen State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China China Mobile Financial Technology Co. Ltd. Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789819610679

Face recognition technology has gradually come into wide application in real life. However, in real-life unconstrained scenarios, low-quality images could be matched to unpredictable individuals, thereby affecting the stability of recognition and even causing security problems. Conducting quality assessment on face images before facial recognition can help alleviate these problems by rejecting low-quality samples. In this paper, we propose a Fast Diffusion-model-based Face Image Quality Assessment method (FDif-FIQA). It uses a diffusion model to perturb face images and measures image quality based on the similarity of features before and after the perturbation. The denoising process is transferred from the pixel space to the latent space, thereby reducing the computational cost. We evaluated the performance of this method with multiple mainstream face recognition models on various public datasets. Compared to state-of-the-art methods, our approach demonstrates highly competitive performance and significant improvements in computational efficiency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Face recognition

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