Skill Acquisition Through Interactive Avatars

通过互动化身获得技能的目标是创建一种基于计算机的人形模拟，可以教人类如何移动。这种系统在最后阶段的硬件要求将是一台配备摄像系统的廉价的最先进的个人计算机。化身将能够向其用户演示动作，监控用户对这些动作的执行，并在性能不佳的情况下建议更正。为了有效，化身将考虑到关于人类运动控制组织的神经科学知识和人类在学习过程中的动机。这项研究将在大量应用中发挥作用，包括运动障碍患者(例如中风患者)的康复、运动和锻炼教育、舞蹈指导、儿童保育和特殊需要教育以及互动娱乐业。此外，为该项目开发的技术有可能开创使用“示范教学”的自主机器人控制的新算法，有助于开发针对人类环境的自动监控系统，产生类人计算机模拟，并对生物运动控制和神经系统的功能有新的见解。作为智力的优点，如何从实时动作捕捉中识别和分类人体动作，如何创建熟练的动作，以及如何有效地教授人类，将有必要获得新的理解。理解人类运动的基础研究问题，无论是从运动感知还是从运动生成的角度来看，都是推进人机和人机交互信息技术的核心，也就是创建自主的人工感知和运动系统。对运动学习的内在动机的研究将推动对如何帮助有学习障碍的人类的重要见解，也将推动如何创造能够激励人们与之互动的机器。作为更广泛的影响，该项目的研究将在创造互动环境方面迈出重要的一步，帮助人们的职业和私人生活。这样的技术将很快成为我们世界的主要组成部分，从临床、娱乐和商业场景开始，最后进入私人家庭。了解如何以用户友好的方式创建和教授熟练的动作将有助于构建自主机器人系统，这些系统可以帮助人类、娱乐人类、在危险环境中取代人类、营救人类，或者只是成为同伴

The goal of "Skill Acquisition Through Interactive Avatars" is to create a computer-based humanoid simulation that can teach humans how to move. The hardware requirements for such as system in its final stage would be an inexpensive state-of-the-art personal computer equipped with a camera system. The avatar will be able to demonstrate movements to its user, monitor the execution of these movements by the user, and suggest corrections in case of inadequate performance. In order to be effective, the avatar will take into account neuroscientific knowledge about the organization of human motor control and human motivation during learning. This research will be useful in a large number of applications, including rehabilitation of movement-impaired patients (e.g., stroke-patients), sport and exercise education, dance instruction, childcare and special needs education, and interactive entertainment industry. Additionally, the technology developed for this project has the potential to pioneer new algorithms for autonomous robot control using "teaching from demonstration", to contribute to the development of automated surveillance systems for human environments, to the generation of humanoid computer simulations, and also to gaining new insights into biological motor control and the functioning of the nervous system. As intellectual merits, it will be necessary to gain new understanding of how to recognize and classify human movement from real-time motion capture, how to create skilled movement, and how to teach humans effectively. The basic research problems of understanding human movement, both in terms of movement perception as well as movement generation, are central to advancing information technology in human-computer as well as human-robot interaction, i.e., the creation of autonomous artificial perception and movement systems. Research on intrinsic motivation in motor learning will advance important insights into how to help humans with learning disabilities, but also how to create machines that are motivating to interact with.As broader impact, the research of this project will make important steps towards creating interactive environments that can assist people in their professional and private lives. Such technology will soon become a major component of our world, starting with clinical, entertainment, and business scenarios, and finally finding its way into private households. Understanding how to create and teach skilled movement in a user friendly way will be useful in building autonomous robot systems that can assist humans, entertain humans, replace humans in hazardous environments, rescue humans, or simply become a companion