Artificial Intelligence for Medical Robotics: From Design Acceleration to Intelligent Perception and Control

Artificial intelligence (AI) is rapidly transforming the field of medical robotics, extending its impact beyond traditional perception and control to earlier stages such as system design and modeling. Emerging approaches leverage machine learning to accelerate computationally intensive processes, including finite element analysis (FEA) for soft and continuum surgical robots and computational fluid dynamics (CFD) for medical devices such as blood pumps. In parallel, data-driven methods provide effective alternatives to analytical modeling for complex robotic systems with challenging kinematic and dynamic structures. These advances complement ongoing developments in AI-enabled perception, planning, and intraoperative decision-making. Together, they create new opportunities for improving the efficiency, intelligence, and clinical applicability of medical robotic systems, while also introducing challenges in reliability, interpretability, and integration.This Research Topic aims to systematically explore the role of artificial intelligence across the full lifecycle of medical robotic systems, from design and modeling to real-time operation. This Topic focuses on three key directions. First, AI-driven methods for accelerating design and optimization processes, such as surrogate modeling for FEA and CFD, enabling rapid iteration of soft robots and medical devices. Second, data-driven approaches for modeling complex robotic systems, where conventional analytical methods are insufficient or impractical. Third, the integration of AI into perception, planning, and intraoperative decision-making to enhance autonomy, precision, and human–robot collaboration. By addressing these challenges, this Topic seeks to promote scalable, efficient, and intelligent solutions that facilitate the translation of medical robotics from research prototypes to clinically viable systems.This Research Topic welcomes original research articles, and reviews on the integration of artificial intelligence in medical robotics and related medical devices. Topics of interest include, but are not limited to:(1) AI-accelerated design and optimization (e.g., surrogate models for FEA/CFD);(2) Data-driven modeling of complex robotic kinematics and dynamics;(3) Learning-based control and motion planning;(4) AI-enabled perception and scene understanding in surgical environments;(5) Intraoperative decision-making and context-aware assistance;(6) Human–robot interaction and shared autonomy;(7) Validation, safety, and interpretability of AI in clinical applications.Submissions should emphasize methodological innovation, computational efficiency, or system-level integration, with demonstrated relevance to medical robotics or devices. Experimental validation, simulation studies, and clinically oriented applications are all encouraged. Topic editors: Mengtang Li, Yilun Sun, Yana Roka Moiia Source: https://www.frontiersin.org/research-topics/80835/artificial-intelligence-for-medical-robotics-from-design-acceleration-to-intelligent-perception-and-control