The Visual Control of Grasping

抓取的视觉控制

• 批准号: RGPIN-2017-04088
• 负责人: Goodale, Melvyn
• 金额: $ 9.11万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710104
• 关键词: Visual; Control; Grasping

The human hand is a remarkable piece of engineering. We can reach out and grasp objects with exquisite accuracy - far better than any robot yet developed. One of the things that makes this possible is our keen sense of sight. Prof. Mel Goodale and his colleagues at Western's Brain and Mind Institute are studying how visual information is used in guiding the hand as it reaches out and grasps an object, how previous experience with objects such as tools affects how an object is grasped, how the presence of others with whom we are interacting affects our grasping, and what brain areas are engaged in these different situations. To study how the hand is moving, Prof. Goodale uses special infra-red sensitive cameras to track tiny infra-red lights that have been attached to the fingertips, hand, and wrist. The data from these cameras can then be used to reconstruct the trajectory of the hand and fingers as the grasping movement unfolds. Previous work in Prof. Goodale's lab has shown that information from the two eyes - binocular vision - plays an important role in the guidance of these movements. But there are other sources of information as well, including the motion of the world on our eyes as we move around and a whole host of cues called 'pictorial cues to depth'. These latter cues - perspective, familiar size, occlusion, shadows, and texture gradients - have been exploited by artists for centuries to depict a three-dimensional world on a two-dimensional canvas. Dr. Goodale and his team are exploring the role of all these different cues in the planning and control of grasping movements of the hand - and how these cues interact with previous experience and knowledge about the world. He is particularly interested in size constancy, the fact that the hand opens the same amount for a goal object independent of its actual distance from the body. He hopes to explore the distance cues that are critical for this 'grip constancy' and whether or not these cues are shared with perceptual size constancy'. He is also looking at how we cope with visual illusions of size - and has already shown that illusions that deceive our eyes rarely fool our grasping hand! Recently, Dr. Goodale has begun to use brain imaging (functional magnetic resonance imaging, or fMRI, and electroencephalography, or EEG) to explore how the brain computes the size of objects that we are trying to grasp and selects the appropriate hand posture when we pick up a tool. Finally, his team is study the subtle differences in the movements we make when we grasp objects in order to hand them to others or to show others how to pick up an object. This work is not only providing basic information about how vision is used to control the human hand but is also helping in the design of better systems for controlling robot hands and for more efficient and transparent human-machine interfaces. This would not be the first time that biology has provided engineering with some useful lessons in design.

人手是一项非凡的工程作品。我们可以以极高的精确度伸出手并抓住物体——远比迄今为止开发的任何机器人都要好。使这成为可能的因素之一是我们敏锐的视觉。西方大脑与思维研究所的梅尔·古德尔教授和他的同事正在研究如何使用视觉信息来引导手伸出并抓住物体，以前对工具等物体的经验如何影响物体的抓握方式，与我们互动的其他人的存在如何影响我们的抓握，以及在这些不同的情况下哪些大脑区域参与其中。为了研究手是如何移动的，古德尔教授使用特殊的红外敏感相机来跟踪附着在指尖、手和手腕上的微小红外光。然后，来自这些摄像机的数据可用于重建抓取运动展开时手和手指的轨迹。 古德尔教授实验室之前的工作表明，来自两只眼睛的信息（双眼视觉）在引导这些运动中发挥着重要作用。但还有其他信息来源，包括当我们四处走动时，我们眼中的世界运动以及一系列被称为“深度图像线索”的线索。后面这些线索——透视、熟悉的尺寸、遮挡、阴影和纹理渐变——几个世纪以来一直被艺术家们用来在二维画布上描绘三维世界。古德尔博士和他的团队正在探索所有这些不同线索在规划和控制手部抓取动作中的作用，以及这些线索如何与以前的经验和关于世界的知识相互作用。他对尺寸恒定性特别感兴趣，即手对于目标物体张开相同的量，而与它与身体的实际距离无关。他希望探索对于这种“握力恒定性”至关重要的距离线索，以及这些线索是否与感知尺寸恒定性共享。 他还在研究我们如何应对大小的视觉错觉——并且已经表明，欺骗我们眼睛的错觉很少能欺骗我们抓握的手！最近，古德尔博士开始使用脑成像（功能性磁共振成像（fMRI）和脑电图（EEG））来探索大脑如何计算我们试图抓住的物体的大小，并在我们拿起工具时选择合适的手部姿势。最后，他的团队正在研究当我们抓住物体以将其交给他人或向其他人展示如何拿起物体时所做出的动作的细微差别。这项工作不仅提供了有关如何使用视觉来控制人手的基本信息，而且还有助于设计更好的系统来控制机器人手以及更高效和透明的人机界面。这并不是生物学第一次为工程学提供一些有用的设计经验。