惯性
感知
平衡(能力)
控制理论(社会学)
理论(学习稳定性)
感觉系统
两足动物
计算机科学
人工智能
粘度
机器人
机器人学
动力学(音乐)
仿人机器人
弹道
控制(管理)
动平衡
模拟
心理学
转动惯量
计算机视觉
物理医学与康复
运动(音乐)
电动机控制
认知心理学
空格(标点符号)
控制工程
绝对时间和空间
时间知觉
人机交互
转化式学习
控制系统
视觉感受
iCub
体感系统
适应(眼睛)
虚拟机
作者
Paul Belzner,Patrick A. Forbes,Calvin Kuo,Jean-Sébastien Blouin,Paul Belzner,Patrick A. Forbes,Calvin Kuo,Jean-Sébastien Blouin
出处
期刊:Science robotics
[American Association for the Advancement of Science (AAAS)]
日期:2025-11-26
卷期号:10 (108)
标识
DOI:10.1126/scirobotics.adv0496
摘要
Effective control of bipedal postures relies on sensory inputs from the past, which encode dynamic changes in the spatial properties of our movement over time. To uncover how the spatial and temporal properties of an upright posture interact in the perception and control of standing balance, we implemented a robotic virtualization of human body dynamics to systematically alter inertia and viscosity as well as sensorimotor delays in 20 healthy participants. Inertia gains below one or negative viscosity gains led to larger postural oscillations and caused participants to exceed virtual balance limits, mimicking the disruptive effects of an additional 200-millisecond sensorimotor delay. When balancing without delays, participants adjusted their inertia gains to below one and viscosity gains to negative values to match the perception of balancing with an imposed delay. When delays were present, participants increased inertia gains above one and used positive viscosity gains to align their perception with baseline balance. Building on these findings, 10 naïve participants exhibited improved balance stability and reduced the number of instances they exceeded the limits when balancing with a 200-millisecond delay compensated by inertia gains above one and positive viscosity gains. These results underscore the importance of innovative robotic virtualizations of standing balance to reveal the interconnected representations of space and time that underlie the stable perception and control of bipedal balance. Robotic manipulation of body physics offers a transformative approach to understanding how the nervous system processes spatial information over time and could address clinical sensorimotor deficits associated with delays.
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