Design and Evaluation of a Compliant Quasi Direct Drive End-effector for Safe Robotic Ultrasound Imaging

[2410.03086] Design and Evaluation of a Compliant Quasi Direct Drive End-effector for Safe Robotic Ultrasound Imaging Skip to main content Search Submit Donate Log in Computer Science > Robotics arXiv:2410.03086 (cs) [Submitted on 4 Oct 2024 ( v1 ), last revised 25 Aug 2026 (this version, v2)] Title: Design and Evaluation of a Compliant Quasi Direct Drive End-effector for Safe Robotic Ultrasound Imaging Authors: Danyi Chen , Ravi Prakash , Vincent Y. Wang , Zacharias Chen , Sarah Dias , Daniel M. Buckland , Leila J. Bridgeman , Siobhan R. Oca , Brian P. Mann View PDF HTML (experimental) Abstract: Robot-assisted ultrasound scanning promises to advance autonomous and accessible medical imaging. However, ensuring patient safety and compliant human-robot interaction during probe contact poses a significant challenge. Most existing systems either have high mechanical stiffness or trade performance for compliance. This paper presents a novel compliant end-effector designed to mount on robotic arms for safe and accurate robotic ultrasound imaging, using a quasi-direct drive actuator to achieve passive mechanical compliance and precise active force control. To evaluate the end-effector's performance, we developed an ex vivo dynamic motion simulator platform for contact and scanning testing on tissue under simulated movements. The end-effector was evaluated against a UR3e robot arm using conventional force control strategies as a baseline. Single-point contact experiments from 2.5 N to 15 N show that the end-effector reduced force tracking RMS error by 80.1% on average. Trajectory scanning experiments at different speeds showed an average of 68.0% reduction in force tracking error. Statistically significant improvements were observed in four of six quantitative image quality and stability metrics using the end-effector. This work presents a novel approach for designing and evaluating compliant end-effectors, with the goal of improving safety and reliability in robotic ultrasound. Subjects: Robotics (cs.RO) Cite as: arXiv:2410.03086 [cs.RO] (or arXiv:2410.03086v2 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2410.03086 Focus to learn more arXiv-issued DOI via DataCite Journal reference: IEEE Trans. Med. Robot. Bionics 8(3) (2026) 1383-1395 Related DOI : https://doi.org/10.1109/TMRB.2026.3699216 Focus to learn more DOI(s) linking to related resources Submission history From: Danyi Chen [ view email ] [v1] Fri, 4 Oct 2024 02:14:10 UTC (4,166 KB) [v2] Tue, 25 Aug 2026 00:19:07 UTC (5,961 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.RO < prev | next > new | recent | 2024-10 Change to browse by: cs References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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