CAREER: Advancing Autonomy for Soft Tissue Robotic Surgery and Interventions

点击翻译按钮获取中文摘要

The research supported by this Faculty Early Career Development (CAREER) grant will make contributions to our fundamental knowledge in robotics and autonomy related to healthcare. Autonomous robotic surgery systems have the potential to significantly improve efficiency, safety, and consistency over current tele-operated robotically assisted surgery. Complication rates of soft tissue surgery such as kidney tumor resections and bowel surgery reach up to 18 and 30 percent, respectively. There is a significant learning curve in robotic surgery, surgical outcomes vary greatly between hospitals, and postoperative complications differ significantly by surgeon. This project will enable the development of a new generation of surgical robots with increasing levels of autonomy that reduce complication rates and improve outcomes independent of surgeon’s experience. This research has the potential to democratize access to the highest level of healthcare by providing consistent expert-level results, mitigate the rising healthcare costs by increasing efficiency, and help in future pandemics by protecting healthcare workers. Thus, results from this research will benefit the US society welfare and economy. The multi-disciplinary research and education activities in robotics and autonomy and related diverse set of intellectual communities ranging from computer vision, sensing, artificial intelligence, to healthcare will help to inspire a diverse set of students from groups that have been traditionally underrepresented in science, technology, engineering, and mathematics (STEM) and to substantially increase participation in robotics research. Present day approaches to automated manipulation are unable to emulate highly trained humans in the performance of complex manipulation tasks in varying, unstructured, and deformable environments. These research and experiments on deformable tissue tracking will yield new techniques for identifying and tracking subtle tissue targets in unstructured environments. The research on deformation prediction will produce methodologies for understanding tissue behavior and how to compensate for deformations. The control-design activities of this project will address shortfalls in autonomous robot controllers by providing new strategies maximizing autonomy, while providing fail-safe operation. This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.