CAREER: Quantifying Humanlike Enveloping Grasps

在过去的十年里，我们产生图形图像的能力已经提高到了可以创造出与现实几乎无法区分的想象场景的程度。在这场图形现实主义的进军中，数字人类被称为最后的前沿，人类动画领域也取得了戏剧性的发展。越来越多地使用动作捕捉数据和操纵这些数据的新技术，使我们能够以极高的保真度重现人体动作。视频游戏和电影中图形生成的角色看起来不可思议地真实。暂停开发易于使用的工具来指导数字人类，我们应该很快就会看到数字人类成为可信的用户界面，动画角色将在教育、演示和培训应用中变得更加普遍。如果说数字人类是逼真计算机图形学的最后前沿，那么现实数字人类的最后前沿就是产生可信的手势。人类的手是美丽而复杂的机制，其实用性和适应性令人惊叹。有人认为是我们的手使我们成为人，而手的进化是智力发展的主要因素。然而，在自主数字人类角色中使用手通常是相当不令人信服的。手可以放在单一的冻结姿势，并在可能的情况下避免角色和对象之间的交互。主要的问题是，人类手的几何模型太灵活了。这种灵活性使得即使是训练有素的动画师也很难与手合作，这给创造必须与环境互动的自主角色带来了巨大的挑战。我相信，在数字角色的手部运动方面取得进一步进展的关键是对人类手的解剖进行更详细的考虑。例如，在分析人类抓取时，至关重要的考虑因素包括指垫、手掌和物体之间的接触量；肌肉产生或抵抗任务的能力；以及手指和肌肉的稳定作用。然而，无论是在机器人学还是计算机图形学领域，这些问题都没有在抓取综合研究中得到探索。为了追求数字字符可信的手部使用的目标，我们提出了一个基于解剖学的人类手势模型。特别是，我们提出了一种基于肌腱的类人包络抓取的质量衡量标准，我们计划评估这一质量衡量标准(1)区分抓取的能力，(2)作为抓持力的预测器，以及(3)用于抓取获得的建模。由于对人体解剖学的高度重视，这项研究有可能在人机工程学(工具设计)、机器人学(机器人手设计)和人类学(研究人类手的进化和工具使用)等领域产生额外的影响。这项提案的教育部分侧重于本科生的教学和辅导。研究思路、技术和成果将被纳入布朗大学的一门课程，吸引本科生和研究生，并将为他们提供在问题领域学习和实验的机会，该领域是计算几何和数值优化的完美结合，以人体解剖学为基础，以数据为支持。将特别努力将本科生女性纳入研究计划，例如，通过CRA分布式导师计划。研究结果将包括一个样例掌握和作用力的库，以及一个使样例适应新的手和物体几何形状的工具。一旦这项研究发表，数据和工具将在网络上供其他研究人员使用，并将作为创建数字角色的有用资源，用于教育、娱乐和培训应用程序。

Over the past decade, our ability to produce graphicalimages has improved to the extent that we can createimaginary scenes that are virtually indistinguishable fromreality. Digital humans have been called the last frontierin this march to graphical realism, and the area of humananimation has also seen dramatic developments. Increasinguse of motion capture data and new techniques formanipulating that data allow us to reproduce human motion atan extremely high level of fidelity. Graphically generatedcharacters in video games and films can seem uncannily real.Pending the development of easy-to-use tools for directingdigital humans, we should soon see digital humans asplausible user interfaces, and animated characters willbecome much more prevalent in education, demonstration, andtraining applications. If digital humans are the lastfrontier in realistic computer graphics, the last frontierin realistic digital humans is generating believable handmotion. Human hands are beautiful and complex mechanisms,amazing in their utility and adaptability. It is argued thatit is our hands that make us human, and that hand evolutionwas a primary factor in the development of intelligence.Hand use in autonomous digital human characters, however, isgenerally quite unconvincing. Hands may be placed in asingle frozen pose, and interaction between characters andobjects is avoided when possible. The main problem is thatgeometric models of the human hand have far too muchflexibility. This flexibility makes working with handsdifficult even for trained animators, and it poses atremendous challenge for creating autonomous characters thatmust interact with their environment. I believe that the keyto making further progress in hand motion for digitalcharacters is much more detailed consideration of theanatomy of the human hand. In analysis of human grasps, forexample, critically important considerations include theamount of contact between finger pads, palm, and object; theability of muscles to produce or resist task force; and thestabilization roles of fingers and muscles, yet none ofthese issues have been explored in grasp synthesis researchin either the robotics or computer graphics communities. Inpursuit of the goal of believable hand use for digitalcharacters, we propose an anatomy-based model of humangrasping. In particular, we propose a tendon-based qualitymeasure for humanlike enveloping grasps, and we plan toevaluate this quality measure (1) for ability todiscriminate between grasps, (2) as a predictor of graspforces, and (3) for use in modeling grasp acquisition.Because of the strong emphasis on human anatomy, thisresearch has the potential for additional impact outsidegraphics and animation in areas including ergonomics (tooldesign), robotics (robot hand design), and anthropology(research in human hand evolution and tool use). Theeducational portion of this proposal focuses on teaching andmentoring of undergraduates. The research ideas, techniques,and results will be incorporated into a course at Brown thatattracts both un-dergraduate and graduate students, and willprovide them with an opportunity to learn and experiment ina problem domain that is a nice mix of computationalgeometry and numerical optimization, grounded in humananatomy and supported by data. A special effort will be madeto include undergraduate women in the research program, forexample, through the CRA Distributed Mentor Program.Research results will include a library of example graspsand applied forces, as well as a tool for adapting theexamples to new hand and object geometries. Once thisresearch is published, the data and tools will be madeavailable to other researchers on the web, and should serveas a useful resource for creating digital characters foreducation, entertainment, and training applications.