Collection
Focused Section on Advances in Robotics and Artificial Intelligence for Minimally Invasive Surgery
In recent decades, robot-assisted minimally invasive surgery has witnessed remarkable progress, driven by cutting-edge technologies like artificial intelligence, advanced imaging technologies, and smart robotics. These advancements have paved the way for more clinically applicable robotic surgical applications. However, there remain challenges related to safety, intelligence, and effectiveness that can be addressed through the development of advanced robotic solutions. This special issue aims to showcase recent advancements, address challenges, and explore novel solutions in the fields of robot-assisted minimally invasive surgery, including novel mechanisms, sensing, perception, and control approaches to promote the applications of surgical robotics. Potential topics of interests for this focus section include but are not limited to:
• Novel mechanisms, mechatronics, sensors, and actuators for surgical robotics
• Continuum/soft robots for enhanced surgical performance and versatility
• Force sensing/feedback technologies and haptic interfaces for precise and immersive surgeries
• Image-guided robot-assisted minimally invasive interventions and surgeries
• Machine learning and reinforcement learning applications in robot-assisted surgery
• Real-time perception and decision-making algorithms for surgical robots
• Human-robot interaction and collaboration in surgical environments
• Integration of emerging technologies (e.g., AI, VR/AR) in robotic surgery
• Simulation-based training and skill assessment for robot-assisted surgery
• Intelligent automation and autonomy in surgical robotics
• Advancements in surgical planning and navigation using robotic systems
Editors
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Hao Su
North Carolina State University, US hao.su796@ncsu.edu
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Kun Bai
Huazhong University of Science and Technology, China kbai@hust.edu.cn
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Yue Chen
Georgia Institute of Technology, US yue.chen@bme.gatech.edu
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Zhenglong Sun
The Chinese University of Hong Kong (Shenzhen), China sunzhenglong@cuhk.edu.cn
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Long Wang
Stevens Institute of Technology, US lwang4@stevens.edu
