About this Research Topic
Surgical robots have made remarkable progress in the past two decades, and at least 3 million patients have been treated with robotic surgeries. Despite the remarkable commercial success of surgical robots, more and more challenging research problems have been identified and a broad spectrum of researchers are attracted to this field with the goal of delivering better surgical outcomes.
Surgical robotics are intrinsically challenging because these robots work in dynamic and unstructured environments and constantly interact with human objects. Moreover, users of surgical robots desire more efficient and reliable performance, decreased costs, improved outputs, and broader applicability of robotic surgery. In order to achieve these goals exploring neural and bioinspired mechanical design and bioinspired methods for control, planning and optimization has great potential to fundamentally improve performance of surgical robots. On the other hand, promoting the community construction of shared platforms and collaborative study can facilitate the development of surgical robot research.
This Research Topic is based on a NSF funded project and aims to promote both the construction of shared platforms and collaborative study and the exploration of applying neuro and bioinspired design and methods for improving surgical robots’ performance. The Topic is a platform for disseminating new findings in the surgical robotics and neuroscience communities. It focuses on applying neuro and bioinspired methods to challenging problems in robotic surgeries, including: robotic surgery planning and optimization, surgical robot control, robotic surgery autonomy and surgical outcome and safety improvement.
The areas of interest include but are not limited to:
• Robotic Surgery Planning and Optimization
• Rigid Surgical Robots and Bioinspired Control
• Flexible Surgical Robots Modeling and Control
• Autonomy in Robotic Surgery
• Learn from Demonstration in Surgical Robotics
• Neuro and Bioinspired Methods for Improving Surgical Outcomes
• Share Platforms and Collaborative Study for Surgical Robot Research
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