Eye-hand Coordination: Exploring How and When perception and action interact.

眼手协调：探索感知和行动如何以及何时相互作用。

• 批准号: RGPIN-2018-04964
• 负责人: Marotta, Jonathan
• 金额: $ 2.11万
• 依托单位: University of Manitoba
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=764078
• 关键词: Eye; hand; Coordination; Exploring; How

Humans reach out and grasp objects with amazing accuracy. Whether we are picking up a cup of coffee, driving a car, or working on a computer, almost every action we make is guided and checked by vision. Where we look is not random, but rather an active process by the visual system to seek out information relevant to the task at hand. Historically, most investigations of eye-hand coordination have involved reaching out to pick up simple, stationary blocks. This research has moved us towards a better understanding of how the systems controlling perception and action interact, but does not properly capture the complex dynamics of the perceptual and motor interactions seen in our everyday lives. Modern applications like gaming and robotics are increasingly relying on natural movements in dynamic visual scenes. An understanding of how the brain solves these complex scenarios would have immediate practical implications. Dr. Marotta and his lab at the University of Manitoba take an innovative, ecologically focused approach that better reflects the dynamic nature of the interactions between perception and action by utilizing paradigms that investigate a wide range of factors including not just vision but proprioception (the perception of the movements and position of the body), and not just grip formation but object lifting.To study how vision is used to control the movements of the hand and arm, Dr. Marotta uses specialized motion-tracking systems that follow where the eyes are looking while simultaneously recording the path of the arm, hand, and fingers during a reach. Over the next 5 years, he and his team will (1) determine how the expected movement of a target influences where we look and how we grasp, (2) evaluate the effects of the availability and timing of visual information on visually guided action and, (3) investigate not only how we utilize visual information but also perception of the body's movements to guide our actions. This fundamental research will provide a clearer understanding of what information we use, and when we use it, to select where we look at and grasp an object providing us with critical insight into how the brain is responsible for this important skill. By including more of our lived experiences into investigations of perception and action, Dr. Marotta's research will create new ecologically focused pathways to research. This research will have applications for gaming development, sports training, the military and spaceflight. It will also assist in the creation of more efficient control systems for robotics, particularly when information about an object has to be determined without assistance from the operator (e.g. devices for the blind or physically impaired). Dr. Marotta provides his trainees with skills needed to lead the advancement of our understanding of perception and action, and to supply robotics engineers with information needed to develop systems to work in the real world.

人类以惊人的准确性伸手抓住物体。无论我们是拿起一杯咖啡，驾驶汽车，还是在电脑上工作，我们所做的几乎每一个动作都是由视觉引导和检查的。我们看的地方不是随机的，而是视觉系统主动寻找与手头任务相关的信息的过程。从历史上看，大多数关于眼手协调的研究都涉及到伸手去拿简单的固定物体。这项研究使我们更好地理解了控制感知和动作的系统如何相互作用，但并没有正确地捕捉我们日常生活中感知和运动相互作用的复杂动态。游戏和机器人等现代应用越来越依赖于动态视觉场景中的自然运动。了解大脑如何解决这些复杂的场景将具有直接的实际意义。马洛塔博士和他在马尼托巴大学的实验室采用了一种创新的、以生态为重点的方法，通过利用研究包括视觉和本体感受在内的广泛因素的范式，更好地反映了感知和行动之间相互作用的动态本质（对身体运动和位置的感知），而且不仅仅是抓握的形成，还有物体的举起。为了研究视觉是如何用来控制手和手臂的运动的，马洛塔博士使用专门的运动跟踪系统，跟踪眼睛所看的地方，同时记录手臂、手和手指在伸手过程中的路径。在接下来的5年里，他和他的团队将（1）确定目标的预期运动如何影响我们的视线和抓握方式，（2）评估视觉信息的可用性和时间对视觉引导行动的影响，（3）不仅研究我们如何利用视觉信息，还研究我们如何利用身体运动的感知来指导我们的行动。这项基础研究将更清楚地了解我们使用什么信息，以及我们何时使用它，以选择我们在哪里看和抓住一个物体，为我们提供关键的洞察力，让我们了解大脑如何负责这项重要的技能。通过将我们更多的生活经验纳入对感知和行动的研究，Marotta博士的研究将创造新的生态研究途径。这项研究将应用于游戏开发，运动训练，军事和航天。它还将有助于创建更有效的机器人控制系统，特别是当必须在没有操作员帮助的情况下确定有关对象的信息时（例如盲人或身体受损者的设备）。马洛塔博士为他的学员提供所需的技能，以引领我们提高对感知和行动的理解，并为机器人工程师提供开发在真实的世界中工作的系统所需的信息。