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Online Decision-Making and Control During Human-Human Interactions

人与人交互过程中的在线决策和控制

基本信息

批准号：
2146888
负责人：
Joshua Cashaback
金额：
$ 59.21万
依托单位：
University of Delaware
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-15 至 2025-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2146888&HistoricalAwards=false
关键词：
Online Decision Making Control During

项目摘要

Research on human motor behavior has largely focused on how individuals control their movement. Yet human survival has depended on our ability to interact with others, both cooperatively and competitively. Understanding how humans collaborate or compete in motor tasks is highly relevant across many facets of society, such as medical rehabilitation, teamwork in the military or sport, robotics, and human-robot interaction. Despite its ubiquity and importance to daily life, how humans physically interact with one another remains poorly understood. This project can make important contributions towards the development of biologically inspired control systems, aligning with the PIs' long-term goal of developing more effective biologically inspired robot-guided neurorehabilitation systems that can seamlessly interact with humans.The investigators use the theoretical frameworks of decision sciences and optimal feedback control to explore how multiple interacting humans use vision and touch to make rapid decisions and coordinate their actions. Human pairs will be immersed in a state-of-the-art virtual reality and robotics suite that allows individuals to sense their partner’s actions visually and haptically while they perform either a collaborative or competitive motor task. In addition to healthy participants, the investigators also consider a stroke population in order to gain causal insight into how the nervous system weighs visual and haptic feedback when sensory information becomes sparse due to brain injury. The blend of experimental work and computational modeling involving both healthy and clinical populations will allow a better understanding of the mechanisms that underpin emergent interactive behavior. The investigators also have a strong commitment to diversity and inclusion and plan include undergraduates and high school students in the research.This project is jointly funded by the Perception, Action, and Cognition (PAC) Program, the Established Program to Stimulate Competitive Research (EPSCoR), the Disabilities and Rehabilitation Engineering (DARE) Program, and the Mind, Machine and Motor Nexus (M3X) Program.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.

对人类运动行为的研究主要集中在个人如何控制自己的运动。然而，人类的生存取决于我们与他人互动的能力，无论是合作还是竞争。了解人类如何在运动任务中协作或竞争与社会的许多方面都高度相关，例如医疗康复、军事或体育团队合作、机器人技术以及人机交互。尽管它无处不在并且对日常生活很重要，但人类如何与彼此进行身体互动仍然知之甚少。该项目可以为仿生控制系统的开发做出重要贡献，符合PI的长期目标，即开发更有效的仿生机器人引导的神经康复系统，可以与人类无缝交互。研究人员利用决策科学和最优反馈控制的理论框架来探索多个交互的人类如何利用视觉和触觉来做出快速决策并协调他们的行动。人类配对将沉浸在最先进的虚拟现实和机器人套件中，使个人在执行协作或竞争性运动任务时能够通过视觉和触觉感知伴侣的动作。除了健康参与者之外，研究人员还考虑了中风人群，以便深入了解当感觉信息因脑损伤而变得稀疏时，神经系统如何权衡视觉和触觉反馈。涉及健康和临床人群的实验工作和计算模型的结合将有助于更好地理解支撑新兴交互行为的机制。研究人员还坚定地致力于多样性和包容性，并计划让本科生和高中生参与研究。该项目由感知、行动和认知 (PAC) 计划、刺激竞争性研究既定计划 (EPSCoR)、残疾和康复工程 (DARE) 计划以及思维、机器和运动联系 (M3X) 计划共同资助。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。