[Submitted on 8 Jul 2026]
Title:In vivo feasibility study of humanoid robots in surgery
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Abstract:Recent advances in actuation, control and learning have rapidly pushed humanoid robots from a distant vision towards near-term real-world deployment. Healthcare is a particularly pressing domain, in which staffing shortages and increasing care demand are widening the gap between clinical workload and available skilled labour. Although current automation has largely focused on digital and logistical tasks, much hospital work remains embodied, requiring mobility, manipulation and safe interaction in human-designed environments. Humanoid form factors offer unique potential, particularly for assisting with surgical tasks. Traditionally, robotic systems for surgery are purpose-built platforms such as Intuitive Surgical's da Vinci Surgical System, and it remains unclear how close current humanoid systems are to meeting the precision, control and safety requirements of minimally invasive surgery. Here we present a systematic evaluation of contemporary humanoid technology for laparoscopic surgical tasks. We develop a humanoid-based laparoscopic teleoperation framework using general-purpose instruments and assess its abilities through benchtop characterization, dry-laboratory user studies spanning diverse surgical experience levels and in vivo porcine studies. Across these evaluations, we quantify technical feasibility, task performance and clinical readiness relative to established surgical platforms. Together, our study provides an evidence-based assessment of current humanoid abilities and limitations for surgical applications, highlighting both their promise and key technical challenges that must be addressed before clinical deployment.
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2607.07972 [cs.RO]
(or arXiv:2607.07972v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2607.07972
arXiv-issued DOI via DataCite (pending registration)
Journal reference: Nature (2026)
Related DOI:
https://doi.org/10.1038/s41586-026-10796-x
DOI(s) linking to related resources
Submission history
From: Zekai Liang [view email] [v1] Wed, 8 Jul 2026 22:57:54 UTC (3,468 KB)
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