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arXiv 2025年

作者： Esfandiari, Mojtaba Du, Pengyuan Wei, Haochen Gehlbach, Peter Munawar, Adnan Kazanzides, Peter Iordachita, Iulian Department of Mechanical Engineering Laboratory for Computational Sensing and Robotics Johns Hopkins University BaltimoreMD21218 United States Department of Computer Science Laboratory for Computational Sensing and Robotics Johns Hopkins University BaltimoreMD21218 United States Laboratory for Computational Sensing and Robotics Johns Hopkins University BaltimoreMD21218 United States Wilmer Eye Institute Johns Hopkins Hospital BaltimoreMD21287 United States

Modeling and controlling cable-driven snake robots is a challenging problem due to nonlinear mechanical properties such as hysteresis, variable stiffness, and unknown friction between the actuation cables and the robot body. This challenge is more significant for snake robots in ophthalmic surgery applications, such as the Improved Integrated Robotic Intraocular Snake (I2RIS), given its small size and lack of embedded sensory feedback. Data-driven models take advantage of global function approximations, reducing complicated analytical models’ challenge and computational costs. However, their performance might deteriorate in case of new data unseen in the training phase. Therefore, adding an adaptation mechanism might improve these models’ performance during snake robots’ interactions with unknown environments. In this work, we applied a model predictive path integral (MPPI) controller on a data-driven model of the I2RIS based on the Gaussian mixture model (GMM) and Gaussian mixture regression (GMR). To analyze the performance of the MPPI in unseen robot-tissue interaction situations, unknown external disturbances and environmental loads are simulated and added to the GMM-GMR model. These uncertainties of the robot model are then identified online using a radial basis function (RBF) whose weights are updated using an extended Kalman filter (EKF). Simulation results demonstrated the robustness of the optimal control solutions of the MPPI algorithm and its computational superiority over a conventional model predictive control (MPC) algorithm. © 2025, CC BY.

关键词： Extended Kalman filters

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The Geometry of Optimal Gait Families for Steering Kinematic Locomoting Systems

arXiv

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arXiv 2025年

作者： Choi, Jinwoo Deng, Siming Justus, Nathan Cowan, Noah J. Hatton, Ross L. Institute Oregon State University CorvallisOR United States Laboratory for Computational Sensing and Robotics Department of Mechanical Engineering Johns Hopkins University BaltimoreMD21218 United States

Motion planning for locomotion systems typically requires translating high-level rigid-body tasks into low-level joint trajectories—a process that is straightforward for car-like robots with fixed, unbounded actuation inputs but more challenging for systems like snake robots, where the mapping depends on the current configuration and is constrained by joint limits. In this paper, we focus on generating continuous families of optimal gaits—collections of gaits parameterized by step size or steering rate—to enhance controllability and maneuverability. We uncover the underlying geometric structure of these optimal gait families and propose methods for constructing them using both global and local search strategies, where the local method and the global method compensate each other. The global search approach is robust to nonsmooth behavior, albeit yielding reduced-order solutions, while the local search provides higher accuracy but can be unstable near nonsmooth regions. To demonstrate our framework, we generate optimal gait families for viscous and perfect-fluid three-link swimmers. This work lays a foundation for integrating low-level joint controllers with higher-level motion planners in complex locomotion systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Motion planning

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Modular ultrasound for flexible longitudinal patient monitoring: Feasibility study

Modular ultrasound for flexible longitudinal patient monitor...

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Medical Imaging 2025: Ultrasonic Imaging and Tomography

作者： Tandri, Ananya Boctor, Emad M. Kang, Jeeun Department of Biomedical Engineering Johns Hopkins University School of Medicine BaltimoreMD United States Laboratory for Computational Sensing and Robotics Johns Hopkins University School of Medicine BaltimoreMD United States Department of Anesthesiology and Critical Care Medicine Johns Hopkins University School of Medicine BaltimoreMD United States

ISBN: (纸本)9781510686021

When it comes to longitudinal patient monitoring, traditional medical ultrasound imaging poses several limitations, namely the inevitable manual scanning and restrictions of spatial resolution due to its fixed hand-held probe form factor. Recently, electronic advances have enabled flexible array fabrication, but its clinical efficacy is limited to the predetermined aperture size. Herein, we propose a position-tracked modular ultrasound (MODUS) framework, allowing clinicians to have an ultrasound array in arbitrary aperture size and on flexible surface curvature, which can maintain utility regardless of patient morphology. We first studied how modular configuration affects imaging quality and artifacts in acoustic simulation. A homogenous adult abdominal tissue-mimicking medium was created with point targets placed at abdominal depths up to 24 cm. An arbitrary MODUS array with different configuration for various uniformity, centeredness, and density was simulated on a semi-ellipse shape. Image similarity and mainlobe to grating lobe ratio were evaluated compared to the ground-truth image given by the full aperture. User-dependent error during modular placement was modelled as a gaussian profile, and the comparative evaluation was repeated. Study findings showed that increasing the distance between modules or the irregularity in module placement was associated with a decrease in image similarity metrics, suggesting an impact of grating lobe artifacts. Increased overall aperture width was correlated with improved spatial resolution at increased depths, suggesting better spatial/angular resolution for beamforming. Interestingly, adding modular positional error did not impact image similarity metrics due to statistical maintenance of spatial sampling rate. We also conducted a proof-of-concept study regarding image reconstruction from optical tracking data of single element transducers. Single element 10MHz ultrasound modules attached to 4-point reflective ball markers we

关键词： Neonatal monitoring

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3D-Printed Stainless Steel Electrodes for Advancing Mems Microbial Fuel Cells Toward Sustainable on-chip Energy 38

3D-Printed Stainless Steel Electrodes for Advancing Mems Mic...

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38th IEEE International Conference on Micro Electro mechanical Systems, MEMS 2025

作者： Elhadad, Anwar Li, Guangfa Yang, Jiaqi Liu, Dehao Choi, Seokheun State University of New York at Binghamton Integrated Computational Materials Design Lab Department of Mechanical Engineering BinghamtonNY United States State University of New York at Binghamton Bioelectronics & Microsystems Laboratory Department of Electrical & Computer Engineering BinghamtonNY United States State University of New York at Binghamton Center for Research in Advanced Sensing Technologies and Environmental Sustainability BinghamtonNY United States

ISBN: (纸本)9798331508890

This study introduces a stainless steel microbial anode fabricated via advanced laser powder bed fusion, marking a transformative step in microbial fuel cell (MFC) technology. By leveraging this cutting-edge metal 3D printing approach, we achieve a 3D microporous structure with superior electrical conductivity, outstanding corrosion resistance in aquatic environments, robust mechanical strength, and adaptability for surface modification - essential attributes for sustainable, high-performance MFCs. The assembled MFC demonstrates unparalleled power output, along with exceptional durability and stability over multiple cycles, outperforming existing MFCs based on alternative 3D-printed substrates. This advancement not only solidifies the role of MFCs as a sustainable energy solution for powering on-chip electronics but also opens new avenues for scalable, cost-effective bioelectronic systems that align with the demands of next-generation technology. © 2025 IEEE.

关键词： Corrosion resistance

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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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Toward Dynamic Control of Tendon-Driven Continuum Robots using Clarke Transform

arXiv

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arXiv 2025年

作者： Muhmann, Christian Grassmann, Reinhard M. Bartholdt, Max Burgner-Kahrs, Jessica Continuum Robotics Laboratory Department of Mathematical and Computational Sciences University of Toronto MississaugaONL5L 1C6 Canada Institute of Mechatronic Systems Faculty of Mechanical Engineering Leibniz University Hannover Garbsen30823 Germany

In this paper, we propose a dynamic model and control framework for tendon-driven continuum robots with multiple segments and an arbitrary number of tendons per segment. Our approach leverages the Clarke transform, the Euler-Lagrange formalism, and the piecewise constant curvature assumption to formulate a dynamic model on a two-dimensional manifold embedded in the joint space that inherently satisfies tendon constraints. We present linear controllers that operate directly on this manifold, along with practical methods for preventing negative tendon forces without compromising control fidelity. We validate these approaches in simulation and on a physical prototype with one segment and five tendons, demonstrating accurate dynamic behavior and robust trajectory tracking under real-time conditions. Copyright © 2025, The Authors. All rights reserved.

关键词： Linear control systems

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Robotic Ultrasound-Guided Femoral Artery Reconstruction of Anatomically-Representative Phantoms

arXiv

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arXiv 2025年

作者： Al-Zogbi, Lidia Raina, Deepak Pandian, Vinciya Fleiter, Thorsten Krieger, Axel Department of Mechanical Engineering The Laboratory of Computational Sensing and Robotics Johns Hopkins University BaltimoreMD United States Malone Center for Engineering in Healthcare Whiting School of Engineering Johns Hopkins University BaltimoreMD United States Ross and Carol Nese College of Nursing Pennsylvania State University University ParkPA United States R. Cowley Shock Trauma Center Department of Diagnostic Radiology School of Medicine University of Maryland BaltimoreMD United States

Femoral artery access is essential for numerous clinical procedures, including diagnostic angiography, therapeutic catheterization, and emergency interventions. Despite its critical role, successful vascular access remains challenging due to anatomical variability, overlying adipose tissue, and the need for precise ultrasound (US) guidance. Errors in needle placement can lead to severe complications, restricting the procedure to highly skilled clinicians in controlled hospital settings. While robotic systems have shown promise in addressing these challenges through autonomous scanning and vessel reconstruction, clinical translation remains limited due to reliance on simplified phantom models that fail to capture human anatomical complexity. In this work, we present a method for autonomous robotic US scanning of bifurcated femoral arteries, and validate it on five vascular phantoms created from real patient computed tomography (CT) data. Additionally, we introduce a video-based deep learning US segmentation network tailored for vascular imaging, enabling improved 3D arterial reconstruction. The proposed network achieves a Dice score of 89.21% and an Intersection over Union of 80.54% on a newly developed vascular dataset. The quality of the reconstructed artery centerline is evaluated against ground truth CT data, demonstrating an average L2 deviation of 0.91±0.70 mm, with an average Hausdorff distance of 4.36±1.11mm. This study is the first to validate an autonomous robotic system for US scanning of the femoral artery on a diverse set of patient-specific phantoms, introducing a more advanced framework for evaluating robotic performance in vascular imaging and intervention. © 2025, CC BY-NC-ND.

关键词： Phantoms

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PAROS: Multi-Component Robotic System and an Image-Guided Patient Alignment for Robot-Assisted Ophthalmic Surgery

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IEEE Access 2025年 13卷 85056-85071页

作者： Alikhani, Alireza Nguyen, Van Dai Inagaki, Satoshi Busam, Benjamin Faridpooya, Koorosh Maier, Mathias Gehlbach, Peter Iordachita, Iulian Navab, Nassir Nasseri, M. Ali Zapp, Daniel Klinikum rechts der Isar der Technische Universität München Augenklinik und Poliklinik Munich 81675 Germany Technische Universität München Department of Computer Science Munich 85748 Germany NSK Ltd. Tokyo 141-8560 Japan Rotterdam Eye Hospital BH Rotterdam 3011 Netherlands Wilmer Eye Institute The Johns Hopkins Hospital Baltimore 21287 MD United States Johns Hopkins University Laboratory for Computational Sensing and Robotics Baltimore 21218 MD United States University of Alberta Department of Biomedical Engineering Edmonton T6G 2R3 AB Canada

Advancements in robot-assisted eye surgery have significantly enhanced precision in delicate procedures by enabling controlled movement of surgical instruments through a small entry point (trocar) placed on the outer layer of the eye (sclera). However, before these procedures can begin, the robot must first be prepared, draped, and calibrated. Then, it is positioned near the patient, where precise patient alignment is performed. Finally, the system ensures accurate alignment between the surgical instrument and the trocar, a critical step for safe and effective instrument insertion and surgical execution. Despite these advancements, integrating robotic systems into clinical practice remains challenging. The current manual preparation and alignment process is time-consuming and error-prone, emphasizing the need for a more automated and adaptive solution. Patient alignment time has been identified as a key factor differentiating robot-assisted and manual surgeries in overall procedure duration, with robot preparation and patient alignment extending surgery time by an average of 51 ± 6 minutes compared to manual methods. To address these challenges, this paper introduces a multi-component robotic system combined with an image-guided patient alignment methodology designed to reduce preparation and alignment time in robotic eye surgery while maintaining surgical efficiency. The robotic system consists of a 2D-Cart carrying a 4-degree-of-freedom (DOF) frame robot holding a 5-DOF micro-manipulator. It utilizes an image-guided, multi-stage alignment approach, enabling the system to efficiently be localized and stabilized in an optimal position beside the surgical bed and ensuring precise and adaptive positioning relative to the patient in the surgical draped condition. The proposed end-to-end robotic system preparation and patient alignment are validated through a user study involving eight medical experts in a simulated surgical environment using a draped phantom eye. The r

关键词： Clinical Integration in Medical robotics Medical Robots and Systems Surgical robotics: Planning

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Leveraging Semantic Graphs for Efficient and Robust LiDAR SLAM

arXiv

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arXiv 2025年

作者： Wang, Neng Lu, Huimin Zheng, Zhiqiang Wang, Hesheng Liu, Yun-Hui Chen, Xieyuanli College of Intelligence Science and Technology National Key Laboratory of Equipment State Sensing and Smart Support National University of Defense Technology China IRMV Lab Department of Automation Shanghai Jiao Tong University China T Stone Robotics Institute Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

Accurate and robust simultaneous localization and mapping (SLAM) is crucial for autonomous mobile systems, typically achieved by leveraging the geometric features of the environment. Incorporating semantics provides a richer scene representation that not only enhances localization accuracy in SLAM but also enables advanced cognitive functionalities for downstream navigation and planning tasks. Existing point-wise semantic LiDAR SLAM methods often suffer from poor efficiency and generalization, making them less robust in diverse real-world scenarios. In this paper, we propose a semantic graph-enhanced SLAM framework, named SG-SLAM, which effectively leverages the geometric, semantic, and topological characteristics inherent in environmental structures. The semantic graph serves as a fundamental component that facilitates critical functionalities of SLAM, including robust relocalization during odometry failures, accurate loop closing, and semantic graph map construction. Our method employs a dual-threaded architecture, with one thread dedicated to online odometry and relocalization, while the other handles loop closure, pose graph optimization, and map update. This design enables our method to operate in real time and generate globally consistent semantic graph maps and point cloud maps. We extensively evaluate our method across the KITTI, MulRAN, and Apollo datasets, and the results demonstrate its superiority compared to state-of-the-art methods. Our method has been released at https://***/nubot-nudt/SG-SLAM. Copyright © 2025, The Authors. All rights reserved.

关键词： Graph theory

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Image-Goal Navigation Using Refined Feature Guidance and Scene Graph Enhancement

arXiv

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arXiv 2025年

作者： Feng, Zhicheng Chen, Xieyuanli Shi, Chenghao Luo, Lun Chen, Zhichao Liu, Yun-Hui Lu, Huimin The College of Intelligence Science and Technology The National Key Laboratory of Equipment State Sensing and Smart Support National University of Defense Technology China Zhejiang University China Jiangxi University of Science and Technology China The T Stone Robotics Institute Department of Mechanical and Automation Engineering The Chinese University of Hong Kong China

In this paper, we introduce a novel image-goal navigation approach, named RFSG. Our focus lies in leveraging the fine-grained connections between goals, observations, and the environment within limited image data, all the while keeping the navigation architecture simple and lightweight. To this end, we propose the spatial-channel attention mechanism, enabling the network to learn the importance of multi-dimensional features to fuse the goal and observation features. In addition, a self-distillation mechanism is incorporated to further enhance the feature representation capabilities. Given that the navigation task needs surrounding environmental information for more efficient navigation, we propose an image scene graph to establish feature associations at both the image and object levels, effectively encoding the surrounding scene information. Cross-scene performance validation was conducted on the Gibson and HM3D datasets, and the proposed method achieved state-of-the-art results among mainstream methods, with a speed of up to 53.5 frames per second on an RTX3080. This contributes to the realization of end-to-end image-goal navigation in real-world scenarios. The implementation and model of our method have been released at: https://***/nubot-nudt/RFSG. Copyright © 2025, The Authors. All rights reserved.

关键词： Image enhancement

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