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Collaborative Research: Learning to Control Dynamically Complex Objects

协作研究：学习控制动态复杂对象

基本信息

批准号：
1825942
负责人：
Dagmar Sternad
金额：
$ 34.92万
依托单位：
Northeastern University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-15 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1825942&HistoricalAwards=false
关键词：
Collaborative Research Learning Control Dynamically

项目摘要

Human sensorimotor capabilities vastly out-perform those of modern robots. Prior research suggests that humans achieve skillful movement by exploiting combinations of "dynamic primitives", which are robust building blocks of coordination that simplify control. Interaction with complex objects - such as spreading a tablecloth - requires prediction which, in turn, requires mental representations of the objects and environment. This project explores the extent to which such mental models may also take the form of dynamic primitives. The project team will perform fundamental research exploring: how humans learn to manipulate a complex flexible object through the composition of dynamic primitives; the impact of explicit instruction on the acquisition of the mental models; and whether a primitive-based control structure to be implemented in a robot can achieve skillful manipulation of complex objects and fluid interactions between humans and robot. This project serves the national interest because the resulting understanding of human sensorimotor control and robot control methods may result in improved efficacy of robot-assisted physical rehabilitation after neuromotor injuries such as stroke, where safe physical cooperation with humans is fundamental and mutual learning is of paramount importance. The project will involve an educational component that provides engineering and research methods training to graduate and undergraduate students, as well as STEM outreach to individuals of all ages at the Museum of Science in Boston. Additional efforts will be made to attract and retain women into careers in science and engineering.This research investigates a biomimetic approach to robot control that promise improved human-robot physical interaction during co-manipulation of flexible objects with complex continuum dynamics. Methods include skill acquisition experiments involving expert and novice human subjects to test how mental representations are formed and the extent to which they may be shaped by explicit instruction during training; a theoretical study of how motor learning may be facilitated using mental models based on dynamic primitives vs. lumped mechanical properties; and a study of human-robot co-manipulation of flexible objects wherein dynamic primitives provide the basis not only for robotic control, but also for communication and mutual learning between the human and robot partners. This research promises new insights into the manipulation of complex objects and tools, an area where humans still outperform machines.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.

人类的感觉运动能力大大超过了现代机器人。先前的研究表明，人类通过利用“动态基元”的组合来实现熟练的运动，动态基元是简化控制的协调的鲁棒构建块。与复杂物体的互动--比如铺桌布--需要预测，而预测又需要对物体和环境的心理表征。这个项目探讨了这种心理模型在多大程度上也可以采取动态原语的形式。该项目团队将进行基础研究，探索：人类如何通过动态原语的组成来学习操纵复杂的柔性物体;显式指令对心智模型获取的影响;以及在机器人中实现的基于连续性的控制结构是否可以实现复杂物体的熟练操纵以及人与机器人之间的流体交互。该项目服务于国家利益，因为由此产生的对人类感觉运动控制和机器人控制方法的理解可能会提高神经运动损伤（如中风）后机器人辅助身体康复的疗效，其中与人类的安全身体合作是至关重要的，相互学习是至关重要的。该项目将包括一个教育部分，为研究生和本科生提供工程和研究方法培训，并在波士顿科学博物馆向所有年龄段的人提供STEM外展服务。将作出额外的努力，以吸引和留住妇女进入职业生涯在科学和engineering.This研究探讨了仿生方法，机器人控制，承诺改善人类与机器人的物理交互过程中的柔性物体与复杂的连续动力学的共同操纵。方法包括技能习得实验，涉及专家和新手人类受试者，以测试心理表征是如何形成的，以及它们在训练过程中被明确的指令塑造的程度;如何使用基于动态原语与集中机械特性的心理模型促进运动学习的理论研究;以及对柔性物体的人机协同操作的研究，其中动态基元不仅为机器人控制提供基础，而且还为人类和机器人伙伴之间的通信和相互学习提供基础。这项研究有望为复杂物体和工具的操作提供新的见解，这是人类仍然优于机器的领域。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。