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Cross-Modality Registration using Bone Surface Pointcloud for Robotic Ultrasound-Guided Spine Surgery

Journal of Medical robotics Research 2025年第0期

作者： Ma, Xihan Zhang, Xiao Wang, Yang Nycz, Christopher J. Sungarian, Arno Ji, Songbai Huang, Xinming Zhang, Haichong K. Department of Robotics Engineering Worcester Polytechnic Institute 100 Institute Rd. Worcester 01609 MA United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute 100 Institute Rd. Worcester 01609 MA United States Memorial Medical Center University of Massachusetts 55 N Lake Ave. Worcester 01655 MA United States Department of Biomedical Engineering Worcester Polytechnic Institute 100 Institute Rd. Worcester 01609 MA United States

Image guidance using preoperative magnetic resonance imaging (MRI) and intraoperative ultrasound (US) can improve the outcome of spine surgery. Employing a robotic US system (RUSS) allows the automated acquisition of large 3D US volumes, facilitating accurate registration. However, such registration remains challenging due to the cross-modality discrepancy. To address this issue, we present a pipeline that extracts spine pointclouds from MRI and 3D US to perform per-vertebra registration. Experiments showed a registration accuracy of 1.82 mm in terms of residual root mean square error and 7.02 mm in terms of Chamfer distance. The pipeline exhibits superior robustness to suboptimal initial conditions compared with the two baseline methods. It also demonstrated good time efficiency under real-time conditions, demonstrating the potential applicability in RUSS-guided spine surgeries. © World Scientific Publishing Company.

关键词： cross-modality registration image-guided intervention robotic ultrasound Spine surgery ultrasound

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Mobile Augmented Reality Framework with Fusional Localization and Pose Estimation

arXiv

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arXiv 2025年

作者： Hou, Songlin Lin, Fangzhou Huang, Yunmei Peng, Zhe Xiao, Bin Department of Computer Science Worcester Polytechnic Institute Worcester01609 United States Department of Robotics Engineering Worcester Polytechnic Institute Worcester01609 United States Unprecedented-scale Data Analytics Center Tohoku University Sendai980-8577 Japan Department of Forestry and Natural Resources Purdue University West Lafayette47907 United States Department of Computing The Hong Kong Polytechnic University 999-077 Hong Kong

As a novel way of presenting information, augmented reality (AR) enables people to interact with the physical world in a direct and intuitive way. While there are some mobile AR products implemented with specific hardware at a high cost, the software approaches of AR implementation on mobile platforms(such as smartphones, tablet PC, etc.) are still far from practical use. GPS-based mobile AR systems usually perform poorly due to the inaccurate positioning in the indoor environment. Previous vision-based pose estimation methods need to continuously track predefined markers within a short distance, which greatly degrade user experience. This paper first conducts a comprehensive study of the state-of-the-art AR and localization systems on mobile platforms. Then, we propose an effective indoor mobile AR framework. In the framework, a fusional localization method and a new pose estimation implementation are developed to increase the overall matching rate and thus improving AR display accuracy. Experiments show that our framework has higher performance than approaches purely based on images or Wi-Fi signals. We achieve low average error distances (0.61-0.81m) and accurate matching rates (77%-82%) when the average sampling grid length is set to 0.5m. © 2025, CC0.

关键词： Wi-Fi

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INTEGRATING REINFORCEMENT LEARNING AND AI AGENTS FOR ADAPTIVE ROBOTIC INTERACTION AND ASSISTANCE IN DEMENTIA CARE

arXiv

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arXiv 2025年

作者： Yuan, Fengpei Hasnaeen, Nehal Zhang, Ran Bible, Bryce Taylor, Joseph Riley Qi, Hairong Yao, Fenghui Zhao, Xiaopeng Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States University of Tennessee KnoxvilleTN37996 United States University of North Carolina CharlotteNC28223 United States Tennessee State University NashvilleTN37209 United States

This study explores a novel approach to advancing dementia care by integrating socially assistive robotics, reinforcement learning (RL), large language models (LLMs), and clinical domain expertise within a simulated environment. This integration addresses the critical challenge of limited experimental data in socially assistive robotics for dementia care, providing a dynamic simulation environment that realistically models interactions between persons living with dementia (PLWDs) and robotic caregivers. The proposed framework introduces a probabilistic model to represent the cognitive and emotional states of PLWDs, combined with an LLM-based behavior simulation to emulate their responses. We further develop and train an adaptive RL system enabling humanoid robots, such as Pepper, to deliver context-aware and personalized interactions and assistance based on PLWDs’ cognitive and emotional states. The framework also generalizes to computer-based agents, highlighting its versatility. Results demonstrate that the RL system, enhanced by LLMs, effectively interprets and responds to the complex needs of PLWDs, providing tailored caregiving strategies. This research contributes to human-computer and human-robot interaction by offering a customizable AI-driven caregiving platform, advancing understanding of dementia-related challenges, and fostering collaborative innovation in assistive technologies. The proposed approach has the potential to enhance the independence and quality of life for PLWDs while alleviating caregiver burden, underscoring the transformative role of interaction-focused AI systems in dementia care. Copyright © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

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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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OriSnake: Design, Fabrication, and Experimental Analysis of a 3-D Origami Snake Robot

引用

IEEE robotics and Automation Letters 2018年第3期3卷 1993-1999页

作者： Luo, Ming Yan, Ruibo Wan, Zhenyu Qin, Yun Santoso, Junius Skorina, Erik H. Onal, Cagdas D. Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States

Snake robots offer a useful and unique mobility platform for search-and-rescue applications. However, existing prototypes made of rigid links and joints are hampered by a lack of flexibility that limits their utility in highly cluttered, maze-like environments, and their heavy weight limits their energy-efficiency and performance in three-dimensional (3-D) tasks. To address these challenges, this letter presents a new approach using cylindrical, origami continuum modules driven by internal cables and electric motors, as well as a local feedback control system on each module. Thus, we can distribute actuation, sensing, and control for highly scalable soft robotic continuum origami systems. Using this approach, we develop a 3-D origami robotic snake that is able to locomote using lateral undulation and sidewinding gaits similar to those used by biological snakes. The proposed snake robot is a continuously deformable, lightweight, modular, and low cost robotic system made of a folded thin plastic body. We detail the design, fabrication, and control of this first 3-D origami robotic snake prototype, focusing on the analysis of locomotion parameters for each gait. We experimentally search for the optimal parameters for both types of locomotion, with maximum speeds characterized as 40.5 mm/s (0.1 body-lengths per second) for lateral undulation and 35 mm/s (0.09 body-lengths per second) for sidewinding locomotion. © 2016 IEEE.

关键词： Fabrication

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NONINVASIVE TRANS-CUTANEOUS MONITORING OF ARTERIAL BLOOD-GASES

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IEEE TRANSACTIONS ON BIOMEDICAL engineering 1984年第12期31卷 792-800页

作者： MENDELSON, Y PEURA, RA Biomedical Engineering Program Worcester Polytechnic Institute Worcester MA USA

Valuable clinical and physiological data concerning the function of the cardiopulmonary system can be obtained from continuous monitoring of hemoglobin oxygen saturation (SaO2), oxygen tension (PO2), and carbon dioxide tension (PCO2) in blood. While periodic blood sampling is still used clinically to determine arterial blood gases, it is becoming apparent that the recent introduction of continuous noninvasive monitoring of blood gases can offer many advantages. This paper discusses the historical development and significant accomplishments of various techniques available for transcutaneous blood gas monitoring. Four major areas are reviewed: electrochemistry, spectrophotometry, mass spectrometry, and gas chromatography. For each of these techniques, the theoretical basis, instrumentation, and clinical applications are discussed.

关键词： Monitoring Blood Gases Skin Epidermis Dermis Humans Instruments Carbon dioxide Sampling methods

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Demonstration and experimental validation of plastic-encased resonant ultrasonic piezoelectric actuator for magnetic resonance imaging-guided surgical robots

引用

Journal of engineering and Science in Medical Diagnostics and Therapy 2020年第1期3卷 011002页

作者： Carvalho, Paulo A.W.G. Nycz, Christopher J. Gandomi, Katie Y. Fischer, Gregory S. Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States Mechanical and Robotics Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

Intra-operative medical imaging based on magnetic resonance imaging (MRI) coupled with robotic manipulation of surgical instruments enables precise feedback-driven procedures. Electrically powered nonferromagnetic motors based on piezoelectric elements have shown to be well suited for MRI robots. However, even avoiding ferrous materials, the high metal content on commercially available motors still cause distortions to the magnetic fields. We construct semicustom piezoelectric actuators wherein the quantity of conductive material is minimized and demonstrate that the distortion issues can be partly addressed through substituting several of these components for plastic equivalents, while maintaining motor functionality. Distortion was measured by assessing the root-mean-squared (RMS) change in position of 49 centroid points in a 12.5 mm square grid of a gelatin-filled phantom. The metal motor caused a distortion of up to 4.91 mm versus 0.55 mm for the plastic motor. An additional signal-to-noise-ratio (SNR) drop between motor off and motor spinning of approximately 20% was not statistically different for metal versus plastic (p ¼ 0.36). Copyright © 2020 by ASME

关键词： Magnetic resonance imaging

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Modular drive system for a planetary exploration mobility platform

Modular drive system for a planetary exploration mobility pl...

引用

2012 IEEE International Conference on Technologies for Practical Robot Applications, TePRA 2012

作者： Amato, Joseph L. Anderson, Jon J. Carlone, Thomas J. Fagan, Michael E. Stafford, Kenneth A. Padir, Taskin Robotics Engineering Program Worcester Polytechnic Institute United States

ISBN: (纸本)9781467308557

This paper discusses the design of a modular drive system for a planetary rover, and presents the testing and thermal monitoring results to validate the design. A rover, Oryx 2.0, is designed and developed to serve as a research platform that can transport payloads over rough terrain. One of the key design features is the modular drive system. The mechanical design, communications and control interfaces are discussed. Moreover, EPOS2 motion controllers by Maxon Motor are explored as motor controllers for the drive system as they provide an easy-to-use high level motor control functionality. The paper will outline step-by-step instructions for setting up the EPOS2 libraries and drivers in Linux/Robot Operating System (ROS) environment. The details of testing procedures and results for the motor modules are also provided. © 2012 IEEE.

关键词： Rovers

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Learning cost functions for motion planning of human-robot collaborative manipulation tasks from human -human demonstration

Learning cost functions for motion planning of human-robot c...

引用

2014 AAAI Fall Symposium

作者： Mainprice, Jim Berenson, Dmitry Robotics Engineering Program Worcester Polytechnic Institute United States

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Sampling-based approximate optimal temporal logic planning

Sampling-based approximate optimal temporal logic planning

引用

2017 IEEE International Conference on robotics and Automation, ICRA 2017

作者： Li, Lening Fu, Jie Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States Robotics Engineering Program Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States

ISBN: (纸本)9781509046331

In this paper, we propose a sampling-based policy iteration for optimal planning under temporal logic constraints. The method integrates approximate optimal control, importance sampling, and formal methods. For a subclass of linear temporal logic, the planning problem is transformed to an optimal control problem for a hybrid system where discrete transitions are triggered by linear time events in temporal logic. Instead of solving the Hamilton-Jacobi-Bellman equation, we use policy function approximation to reduce the problem into a search of an optimal weight vector that parametrizes the near-optimal policy for given bases. Then, we incorporate Model Reference Adaptive Search - an importance sampling-based optimization algorithm to perform a sample-efficient search within the parameter space of policy function approximations. Facing the discontinuity in cost function introduced by temporal logic constraints and system dynamics, we introduce 1) a rank function in formal logic specifications to enable sample-efficient search;2) specification-guided basis selection. Under mild technical assumptions, the proposed algorithm converges, with probability one, to a global approximate optimal policy that ensures the satisfaction of temporal logic constraints. The correctness and efficiency of the method are demonstrated through numerical experiments including temporal logic planning for a linear system and a nonlinear mobile robot. © 2017 IEEE.

关键词： Temporal logic

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