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arXiv 2025年

作者： Joshi, Rishikesh Sattar, Junaed Department of Computer Science and Engineering Minnesota Robotics Institute University of Minnesota – Twin Cities MinneapolisMN United States

Reliable human-robot communication is essential for effective underwater human-robot interaction (U-HRI), yet traditional methods such as acoustic signaling and predefined gesture-based models suffer from limitations in adaptability and robustness. In this work, we propose One-Shot Gesture Recognition (OSG), a novel method that enables real-time, pose-based, temporal gesture recognition underwater from a single demonstration, eliminating the need for extensive dataset collection or model retraining. OSG leverages shape-based classification techniques, including Hu moments, Zernike moments, and Fourier descriptors, to robustly recognize gestures in visually-challenging underwater environments. Our system achieves high accuracy on real-world underwater video data and operates efficiently on embedded hardware commonly found on autonomous underwater robots (AUVs), demonstrating its feasibility for deployment on-board robots. Compared to deep learning approaches, OSG is lightweight, computationally efficient, and highly adaptable, making it ideal for diver-to-robot communication. We evaluate OSG’s performance on an augmented gesture dataset and real-world underwater video data, comparing its accuracy against deep learning methods. Our results show OSG’s potential to enhance U-HRI by enabling the immediate deployment of user-defined gestures without the constraints of predefined gesture languages. Copyright © 2025, The Authors. All rights reserved.

关键词： Human robot interaction

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Toward Lung Ultrasound Automation: Fully Autonomous Robotic Longitudinal and Transverse Scans Along Intercostal Spaces

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical robotics and Bionics 2025年第2期7卷 768-781页

作者： Lei, Long Hu, Yingbai Jiang, Zixing Miao, Juzheng Luo, Xiao Zhang, Yu Wang, Qiong Wang, Shujun Li, Zheng Heng, Pheng-Ann The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Chinese University of Hong Kong Multi-Scale Medical Robotics Centre Ltd. Hong Kong The Chinese University of Hong Kong Department of Surgery Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen518055 China The Hong Kong Polytechnic University Department of Biomedical Engineering Hong Kong Chow Yuk Ho Technology Centre for Innovative Medicine Li Ka Shing Institute of Health Sciences Multiscale Medical Robotics Centre Ltd. The Chinese University of Hong Kong Department of Surgery Hong Kong

Lung ultrasound scanning is essential for diagnosing lung diseases. The scan effectiveness critically depends on both longitudinal and transverse scans through intercostal spaces to reduce rib shadowing interference, as well as maintaining the probe perpendicular to pleura for pathological artifact generation. Achieving this level of scan quality often depends heavily on the experience of doctors. Robotic ultrasound scanning shows promise, but currently lacks a direct path planning method for intercostal scanning, and probe orientation does not consider imaging differences between lungs and solid organs. In this paper, we aim to fully automate two fundamental operations in lung ultrasound scanning: longitudinal and transverse scans. We propose pioneering path planning methods along intercostal spaces and innovative solutions for adaptive probe posture adjustment using real-time pleural line feedback, specifically addressing the unique characteristics of lung ultrasound scanning. This ensures the acquisition of high-quality, diagnostically meaningful ultrasound images. In addition, we develop a robotic lung ultrasound system to validate the proposed methods. Extensive experimental results on two volunteers and a chest phantom confirm the efficacy of our methods, and demonstrate the system's feasibility in automated lung ultrasound examinations. Our work lays a solid foundation for automated robotic complete lung scanning. © 2018 IEEE.

关键词： Motion planning

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Crop protection and disease detection using artificial intelligence and computer vision: a comprehensive review

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Multimedia Tools and Applications 2025年第7期84卷 3723-3743页

作者： Shah, Kanish Sushra, Rajat Shah, Manan Shah, Dhairya Shah, Haard Raval, Megh Prajapati, Mitul Software Engineer Walmart SunnyvaleCA United States Atmiya Vidya Mandir Gujarat Surat India Department of Chemical Engineering School of Energy Technology Pandit Deendayal Energy University Gujarat Gandhinagar India Robotics ECE Concentration Northeastern University BostonMA United States Department of Computer Science Concentration in AI Hofstra University HempsteadNY United States Department of Chemical Engineering S. S Agrawal Institute of Engineering & Technology Gujarat Navsari India R &D Engineer Span Inspection Systems Pvt. Ltd Gujarat Gandhinagar India

The technological advancements in the field of agriculture have increased to a great extent in recent years, and many techniques have evolved from other techniques. Some methods are improved or upgraded from the previous versions by implementing a new model or using better hardware devices. This has been helpful for the farmers in increasing crop productivity, and the life expectancy of crops has also increased as the diseases inside or outside the crops can be detected much earlier, and learning at an early stage helps prevent other crops. In this paper, we have presented a study where many varieties of fruits and vegetables have been taken to determine which method was used for a particular crop. By analyzing the various works carried out by the authors, it was inferred that most of the works revolved around image processing and hyperspectral imaging. Due to this, we had also included most of the papers, particularly as the models and hardware components used were much better than other works. Then, a comparative study was done where different fruits and vegetables highlighted the two main areas: the method used and the accuracy obtained. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Crops

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AI Integrated Dialogic Alphabet Zone Board for Kids in Pre-childhood Education

AI Integrated Dialogic Alphabet Zone Board for Kids in Pre-c...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Asif Mahmud Tahsin Faisal M. Akhtaruzzaman Jamal Uddin Tanvin Sachitra Halder Fahim Shahryer Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

The smart Dialogic Alphabet Zone Board (DAZ-Board) aims to address the issue of learning process for pre-childhood education among the children. It is importance to facilitate a healthy and effective environment for early childhood education in shaping a child’s cognitive development, language acquisition, and literacy skills. Traditional teaching methods often fail to engage young learners effectively, leading to limited understanding and retention. On the other hand, dependencies on mobile devices raise the physical and mental health issues. This study introduces an interactive, auditory, and multisensory game board providing a wonderful and healthy experiences in tailoring the developmental needs of children. The objective of this research is to design and develop an interactive alphabet board with necessary sensors, electronics, and controller modules. Moreover, designing a Machine Learning (ML) model for voice-based alphabet recognition is one of the important contributions of this research. Among the results of different ML models, Naïve Bayes Classifier outperforms the most with accuracy ≈ . %. The proposed system will facilitate the preschoolers to learn in modern and interactive way, while keeping away from being addicted to the mobile devices.

关键词： Pediatrics Visualization Accuracy Scalability Education Games Speech recognition Sensors Smart phones Systematic literature review

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Onboard Perception-Assisted High Fidelity Simulation Framework for Autonomous Planetary Soft-Landing

Onboard Perception-Assisted High Fidelity Simulation Framewo...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Alibekov, Ulugbek Banerjee, Avijit Satpute, Sumeet Gajanan Nikolakopoulos, George ERASMUS MUNDUS JOINT MASTER in Intelligent Field Robotic Systems Faculty of Informatics Eötvös Loránd University Budapest Hungary Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents an onboard perception-assisted high-fidelity simulation framework for autonomous planetary soft-landing, enabling visual information processing tightly integrated with advanced onboard guidance system in a realistic simulation environments. Utilizing the open source Unity game engine, a physics-based simulation toolbox integrated with the Robotic Operating System (ROS2), we effectively emulate the motion of spacecraft approaching planetary terrain. The simulation environment features a realistic 3D terrain model and a lander spacecraft equipped with onboard camera to effectively capture detailed local terrain images. The simulation engine accurately captures the spacecraft’s 6-degrees of freedom motion, seamlessly integrating space craft orientation with the associated camera feed while incorporating various illumination conditions using a light source representing the Sun. To demonstrate the efficacy of the framework, we implement a recently developed attitude-constrained minimum jerk guidance algorithm to emulate spacecraft motion. Concurrently, the visual feed from the onboard RGB camera is processed through a gradient extraction-based perception system, providing the visual odometer. This system identifies provably safe landing sites, effectively avoiding potential risks of landing on uneven terrain. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Planetary landers

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OFF-CLIP: Improving Normal Detection Confidence in Radiology CLIP with Simple Off-Diagonal Term Auto-Adjustment

arXiv

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arXiv 2025年

作者： Park, Junhyun Moon, Chanyu Lee, Donghwan Kim, Kyungsu Hwang, Minho Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Electrical Engineering and Computer Science DGIST Korea Republic of Seoul National University Korea Republic of

Contrastive Language-Image Pre-Training (CLIP) has enabled zero-shot classification in radiology, reducing reliance on manual annotations. However, conventional contrastive learning struggles with normal case detection due to its strict intra-sample alignment, which disrupts normal sample clustering and leads to high false positives (FPs) and false negatives (FNs). To address these issues, we propose OFF-CLIP, a contrastive learning refinement that improves normal detection by introducing an off-diagonal term loss to enhance normal sample clustering and applying sentence-level text filtering to mitigate FNs by removing misaligned normal statements from abnormal reports. OFF-CLIP can be applied to radiology CLIP models without requiring any architectural modifications. Experimental results show that OFF-CLIP significantly improves normal classification, achieving a 0.61 Area under the curve (AUC) increase on VinDr-CXR over CARZero, the state-of-the-art zero-shot classification baseline, while maintaining or improving abnormal classification performance. Additionally, OFF-CLIP enhances zero-shot grounding by improving pointing game accuracy, confirming better anomaly localization. These results demonstrate OFF-CLIP’s effectiveness as a robust and efficient enhancement for medical vision-language models. Copyright © 2025, The Authors. All rights reserved.

关键词： Radiology

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Gravity Compensation of the dVRK-Si Patient Side Manipulator based on Dynamic Model Identification

arXiv

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arXiv 2025年

作者： Zhou, Haoying Yang, Hao Deguet, Anton Fichera, Loris Wu, Jie Ying Kazanzides, Peter Department of Robotics Engineering Worcester Polytechnic Institute MA United States Laboratory for Computational Sensing and Robotics JHU MD United States Department of Computer Science Vanderbilt University TN United States Department of Computer Science Johns Hopkins University MD United States

The da Vinci Research Kit (dVRK, also known as dVRK Classic) is anopen-source teleoperated surgical robotic system whose hardware is obtainedfrom the first generation da Vinci Surgical System (Intuitive, Sunnyvale, CA,USA). The dVRK has greatly facilitated research in robot-assisted surgery overthe past decade and helped researchers address multiple major challenges inthis domain. Recently, the dVRK-Si system, a new version of the dVRK which usesmechanical components from the da Vinci Si Surgical System, became available tothe community. The major difference between the first generation da Vinci andthe da Vinci Si is in the structural upgrade of the Patient Side Manipulator(PSM). Because of this upgrade, the gravity of the dVRK-Si PSM can no longer beignored as in the dVRK Classic. The high gravity offset may lead to relativelylow control accuracy and longer response time. In addition, althoughsubstantial progress has been made in addressing the dynamic modelidentification problem for the dVRK Classic, further research is required onmodel-based control for the dVRK-Si, due to differences in mechanicalcomponents and the demand for enhanced control performance. To address theseproblems, in this work, we present (1) a novel full kinematic model of thedVRK-Si PSM, and (2) a gravity compensation approach based on the dynamic modelidentification. © 2025, CC BY.

关键词： Surgical equipment

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Integrating Function and Connection: Two Perspectives to Telepresence Robot Design for Classroom 25

Integrating Function and Connection: Two Perspectives to Tel...

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2025 ACM International Conference on Supporting Group Work, GROUP Companion 2025

作者： Berhane, Roda Akiode, Deo Adejoke Joshi, Swapna Elmimouni, Houda School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Field Robotics Lab Northeastern University BostonMA United States Department of Computer Science University of Manitoba WinnipegMB Canada Information Systems and New Media University of Siegen Siegen Germany

ISBN: (纸本)9798400711879

This study explores robotic telepresence in classrooms, from the perspectives of both the remote students (operators) and their in-person classmates. Analyzing a subset of field study data from 35 participants (22 operators, 13 classmates), we identified differing priorities: operators of the robot emphasize the need for improved functional aspects like camera control, while co-present classmates value social presence, interaction and identification, advocating for features like personalization and effective communication channels. These insights underline the need for telepresence robots that balance functional efficacy with social integration to provide a holistic educational experience. This work, though incomplete, enriches Group and CSCW literature on telepresence robots to facilitate collaborative interactions by highlighting the distinct needs of remote and in-person students, proposing design recommendations for telepresence robots that are technically proficient and socially responsive. © 2025 Copyright held by the owner/author(s).

关键词： Students

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Design and Implementation of an On-Board System for a Spider Robot 1st

Design and Implementation of an On-Board System for a Spider...

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1st International Conference on Computing and Emerging Technologies, ICCET 2023

作者： Nauman, Nasir Mustafa, Hirra Ashraf, Abrar Khalil, Hisham Department of Computer Science Superior University Lahore Pakistan Department of Computer Science Sharif College of Engineering and Technology Lahore Lahore Pakistan Embedded System and Robotics Lab Department of Technology The University of Lahore Lahore Pakistan

ISBN: (纸本)9783031776199

This paper presents the design of a system onboard spider robot for rescue services. The spider has the six-leg walking pattern that contains the total number of 18 servo motors. In order to reduce the payload, the abdomen of the spider is made with RF4 printed circuit board (PCB). Whereas, the abdomen is also used as the main structure of the robot to attach the rest of the system. Wherein, two pulse-width modulations (PWM) module are controlled by Arduino Nano, the Bluetooth module is used for communication link and bulk converter for the power supply. The spider robot is operated with an in-house developed Android application. It has been observed that the spider robot has a stable walking response along with the multiple excise performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Machine design

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A Novel Approach to Continual Knowledge Transfer in Multilingual Neural Machine Translation Using Autoregressive and Non-Autoregressive Models for Indic Languages

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IEEE Access 2025年 13卷 89775-89810页

作者： Sheshadri, Shailashree K. Gupta, Deepa Paul, Biswajit Siva Bhavani, J. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India DRDO Centre for Artificial Intelligence and Robotics CV Raman Nagar Bangalore India

Recent progress in multilingual pre-trained models has significantly improved translation quality for Indic languages. However, extending these models to new languages via fine-tuning or retraining remains computationally costly and often leads to parameter interference, degrading performance on previously learned or typologically distant languages. While continual learning offers a promising alternative for incremental language addition, its application in Indic contexts is still limited and faces challenges in generalization across diverse linguistic settings. To overcome these issues, we propose a Continual Knowledge Transfer (CKT) framework for efficient and scalable multilingual adaptation. CKT is realized in both autoregressive (MNMT) and non-autoregressive (Switch-GLAT) architectures, yielding two variants: MNMT+CKT and Switch-GLAT+CKT. Rather than retraining the entire model, CKT freezes the multilingual base and updates only parameters relevant to the newly added *** innovations include gradient-based knowledge pruning, sequential teacher integration, and dynamic vocabulary expansion for minimizing interference and maximizing cross-lingual retention. Comprehensive evaluations on the IN22-Conv and IN22-Gen benchmark datasets demonstrate that both MNMT+CKT and Switch-GLAT+CKT consistently outperform established baselines, such as IndicTrans2, Google Translate, GPT-4-32K, LLaMA-2-17B, and NLIP-LAB-IITH. The proposed multi-step distillation approach, MNMT+CKT, consistently outperforms conventional fine-tuning and Knowledge Transfer (MNMT+KT) strategies for incremental adaptation of linguistically diverse Indic languages. On IN22-Conv, BLEU improvements range from +4.93 (Kashmiri → English) to +11.48 (Assamese → English) and similar improvements are seen for IN22-Gen. The method also achieves substantial reductions in trainable parameters—19.80% (Nepali) to 66.87% (Kannada)—while enabling up to 4x faster inference when integrated with the Switch-GLAT ar

关键词： Neural machine translation

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