Intelligent Medical Robotics: Advances in Perception, Autonomy, Diagnosis, Treatment and Human-Robot Collaboration

The integration of robotics and artificial intelligence is transforming modern healthcare, from high‑precision surgery to assistive care and hospital automation. Recent advances in computer vision, sensor fusion, and reinforcement learning have enabled robots to perform complex tasks in dynamic medical environments. However, challenges persist in real‑time safety, adaptive decision‑making under uncertainty, and intuitive human‑robot interaction. Bridging these gaps requires close collaboration between engineers, clinicians, and regulatory bodies.This Research Topic aims to collect cutting‑edge contributions that advance the design, control, perception, and clinical deployment of intelligent medical robotic systems. We seek to address key problems such as: how to achieve systematic intelligent diagnosis and treatment by integrating robotic perception, clinical decision support, and patient‑specific adaptation; how to guarantee safety during autonomous subtasks; how to develop shared‑control strategies that respect surgeon or patient intent; and how to validate robotic solutions in real‑world clinical settings. By presenting state‑of‑the‑art methodologies, openly shared datasets, and reproducible pipelines, this collection will accelerate the translation of laboratory prototypes into cost‑effective, user‑friendly, and clinically validated tools. Ultimately, we aim to foster cross‑disciplinary dialogue and set a reference point for roboticists, AI researchers, clinicians, and healthcare policymakers.We invite original research articles studies on topics including but not limited to:• Medical and Biomedical Robotics; • Biomechanics, Sensing and Bio-inspired Control in Rehabilitation and Assistive Robotics;• Robot‑assisted Diagnosis and Intervention; • Control, Teleoperation with Haptic Feedback; • Medical Signal and Image Processing; • Human-System Interaction and Interface; • Sensor Design, and Novel Sensing Systems; • Vision System, Robotic Vision. We strongly encourage submissions demonstrating real‑world testing, open datasets, or reproducible methodologies. Topic editors: Linshuai Zhang, Tao Jiang, Gongjun Yan Source: https://www.frontiersin.org/research-topics/81554/intelligent-medical-robotics-advances-in-perception-autonomy-diagnosis-treatment-and-human-robot-collaboration