NRI: Collaborative Research: Human-Supervised Manipulation of Deformable Objects

所提出的工作的目标是开发算法，使人类监督下的机器人操纵的变形物体下显着的不确定性。可变形物体的操纵在外科手术中是必不可少的，这涉及在相当大的不确定性下对精细和高度可变形组织的复杂操纵，并且在制造中，许多组装任务涉及柔性部件和材料（例如，电缆、纺织品和复合材料）。机器人硬件的最新进展（例如，达芬奇和巴克斯特机器人）已经使机器人操纵可变形物体物理上成为可能，但机器人仍然缺乏必要的算法来执行实际任务时，在这个领域有显着的模型不确定性。该项目将通过其在手术和制造机器人方面的应用产生广泛的社会影响。鲁棒操纵可变形结构的能力是实现智能机器人手术助手的重要先导技术。机器人技术及其医疗应用有可能激励孩子们在STEM领域追求职业生涯，并满足美国不断增长的医疗保健和制造机器人行业的需求。研究活动与教育的整合将强调积极参与研究活动的本科生，并引入新的讲座材料和项目到本科生和研究生课程。此外，还将特别重视从代表性不足的群体中招收合格的学生。拟议的研究的目的是开发算法，使人类监督下的机器人操作的变形物体在很大的不确定性。具体而言，研究将集中在开发自适应复杂性模型建模可变形物体的动力学和相关的不确定性，规划算法的综合勘探和任务执行，控制算法的鲁棒操纵的不确定性下的可变形物体，和算法的机器人操纵的可变形物体的有效的人的监督。该项目的智力价值来自其对机器人建模，规划和控制算法的基本贡献，用于操纵可变形物体。该研究将在机器人操作，不确定性下的运动规划和顺应性操作控制领域产生影响。

The goal of the proposed work is to develop algorithms that enable human-supervised robotic manipulation of deformable objects under significant uncertainty. Manipulation of deformable objects is essential in surgery, which involves complex manipulations of delicate and highly deformable tissue under substantial uncertainty, and in manufacturing, where many assembly tasks involve flexible parts and materials (e.g. cables, textiles, and composites). Recent advances in robot hardware (e.g. the da Vinci and Baxter robots) have made robotic manipulation of deformable objects physically possible but robots still lack the algorithms necessary to perform practical tasks in this domain when there is significant model uncertainty. This project will have broad societal impact through its applications in surgical and manufacturing robotics. The ability to robustly manipulate deformable structures is an important precursor technology towards realizing intelligent robotic surgical assistants. Robotics and its medical applications have the potential to inspire children to pursue careers in STEM fields and meet the needs of America's growing health-care and manufacturing robotics industry. Integration of the research activities with education will emphasize actively involving undergraduates in research activities and introducing new lecture material and projects into undergraduate and graduate courses. Also, special emphasis will be given to recruit qualified students from under-represented groups. The purpose of the proposed research is to develop algorithms that enable human-supervised robotic manipulation of deformable objects under substantial uncertainty. Specifically, the research will focus on developing adaptive complexity models for modeling deformable object dynamics and associated uncertainty, planning algorithms for integrated exploration and task execution, control algorithms for robust manipulation of deformable objects under uncertainty, and algorithms for effective human supervision of robotic manipulation of deformable objects. The intellectual merit of the project comes from its fundamental contributions to robotic modeling, planning, and control algorithms for manipulation of deformable objects. The research will have impact in the fields of robotic manipulation, motion planning under uncertainty, and compliant manipulation control.