ITR: Collaborative Research: Using Humanoids to Understand Humans

点击翻译按钮获取中文摘要

Research in neuroscience and motor psychology has made tremendous progress in generating better understanding of how the human brain generates motor behaviors. At the same time robotics and computer graphics have created increasingly impressive examples of theories and implementations of a variety of movement behaviors, as seen in humanoid robotics and interactive animations and games. Despite this progress, however, a major shortcoming in all these disciplines remains an understanding of how complex movements that we make every day can be created and combined flexibly, robustly, and autonomously. The goal of this project is to develop and evaluate comprehensive information processing models of human motor behavior, to overcome these shortcomings. The PIs will investigate the algorithms and representations (such as what is stored in long term memory) that enable the skilled behavior we see every day, using brain imaging, studies of behavior, and evaluations of our ideas on humanoid robots and in simulation. It brings together a set of researchers who have individually or in small collaborations addressed fragments of this challenge. The PIs have been successful in investigating individual and highly specialized motor tasks, but have not yet integrated a significant number of behaviors such that a robot or simulation could autonomously and robustly interact with a dynamic environment. Members of this team have built biologically inspired locomoting andhumanoid robots that balance; walk and run on both flat terrain, inclines, and stairs at a wide range of speeds; accurately place their feet while walking and running; jump and leap; jump through hoops; perform flips; recover from slips, trips, and stumbles; compliantly interact with humans; throw, catch, hit, and juggle balls; devilstick; and play air hockey. They have received equipment funding to develop a next generation humanoid in collaboration with Sarcos, from the NSF CISE Collaborative Research Resources (Research Infrastructure) Program. This humanoid experimental testbed will allow them to develop and evaluate their proposals as to how behavior is generated much more effectively. In the past, this group and others have focused on modeling single tasks. This project focuses on developing and testing approaches to coordinate many behaviors, and handle behavior selection, multiple tasks, behavioral transitions, and error compensation, making the crucial step from highly specialized investigations to a more general theory of information processing in human motor control.