ITR: Dance, a Programming Language for the Control of Humanoid Robots

机器人在许多商业、工业和军事应用中变得越来越普遍，也越来越重要。这个项目的重点是人形机器人，随着它们的复杂程度的提高，它们变得越来越有用，因为它们可以在专门为人类设计的环境中工作，因为它们使人类更容易与自动化进行交互。这个项目特别关注如何对人形机器人进行编程；也就是说，如何尽可能简单有效地编程他们的动作和互动。重点不是开发机器人运动或传感的新算法。相反，一旦有了算法，我们该如何给机器人编程，让它走路、挥动手臂、拍手或捡起一个物体？如何以一种高级的方式做到这一点，既没有不必要的细节，又有足够的表现力来捕捉所有理想的动作和交互？这项工作的核心是设计一种称为“Dance”的领域特定语言，该语言高度抽象，易于使用，但具有足够的表达能力来描述广泛的有用的机器人动作。舞蹈结合了PI以前在计算机音乐，计算机动画和软件控制领域特定语言方面的工作的想法。例如，Dance使用声明性的基于事件的反应性，使机器人能够对其环境（通过触觉、听觉和视觉传感器）、自身身体（如肢体之间的交互）和内部编程事件（计时器、远程消息、用户命令等）做出响应。创新的语言研究使舞蹈中的行为成为计算对象，使程序能够抽象（聚合）动作序列并评估这些序列的相互作用。该语言也适用于基于形式代数语义的形式推理。基于这个代数的公理，可以证明舞蹈程序的关键运行时属性。提议的工作还包括一个名为“舞蹈工作室”的编程环境，该环境能够模拟并可视化运行的舞蹈程序，使程序员能够在完全部署机器人之前动态调试她的程序。舞蹈语言研究开创了一种控制编程概念，它与许多应用相关，这些应用需要复杂的、聚合的系统行为或操作，并且这些行为必须得到协调和保证。这项研究是耶鲁大学创造“善于社交”的机器人这一更广泛议程的一部分，并为其提供了支持。构建一台能够识别来自人类观察者的社交线索的机器，可以实现更自然的人机交互风格，为机器通过直接观察未经训练的人类讲师来学习创造了可能性，并扩展了机器人系统不断增长的能力。这种社会机器可以作为调查工具来研究人类社会发展的许多方面。例如，一个能够感知识别社会线索的机器人可以用来提供社会反应的定量度量。这一指标可能是自闭症等社会发展障碍的有用诊断工具。事实上，利用人形机器人诊断和治疗自闭症的研究正在耶鲁大学人形机器人项目的更广泛范围内进行。

Robots are becoming increasingly common in, and important to, many commercial, industrial, and military applications. This project focuses on humanoid robots, which are becoming increasingly useful as they advance in sophistication, because they can perform in environments engineered specifically for humans, and because they make it easier for humans to interact with automation. This project focuses specifically on how to program humanoid robots; i.e. how to program their movements and interactions as easily and as effectively as possible. The focus is not on developing new algorithms for robot movement or sensing. Rather, once an algorithm is in hand, how does one program a robot to walk, wave its arms, clap its hands, or pick up an object? How does one do so in a high-level way that is devoid of unnecessary detail, yet is expressive enough to capture all desirable movements and interactions?The core of this effort is the design of a domain-specific language called "Dance" that is highly abstract, easy to use, yet has enough expressive power to describe a wide range of useful robot movements. Dance incorporates ideas from the PI's previous work on domain-specific languages for computer music, computer animation, and software-enabled control. For example, Dance uses declarative event-based reactivity to give a robot the ability to respond to its environment (through tactile, aural, and visual sensors), to its own body (such as interactions between limbs), and to internal programmatic events (timers, remote messages, user commands, and so on). Innovative language research makes behaviors the objects of computation in Dance, which enables programs to abstract over (aggregate) action sequences and evaluate interactions of such sequences. The language is also amenable to formal reasoning based on a formal algebraic semantics. It is possible to prove crucial run-time properties of Dance programs based on the axioms of this algebra. The proposed work also includes a programming environment called "Dance Studio" that has the ability to simulate and thus visualize a running Dance program, enabling a programmer to dynamically debug her programs prior to full robot deployment.Dance language research pioneers a control programming concept that is relevant for many applications in which complex, aggregate system behaviors or maneuvers are required, and in which such behaviors must be coordinated and assured. The research is part of, and supports, a broader agenda at Yale to create "socially adept" robots. Building a machine that can recognize social cues from a human observer allows a more natural human-machine interaction style, creates possibilities for machines to learn by directly observing untrained human instructors, and expands on the growing capabilities of robotic systems. Such social machines can be used as investigative tools to study many aspects of human social development. For example, a robot that is capable of perceptually identifying social cues can be used to provide a quantitative metric of social response. This metric may be a useful diagnostic tool for social development disorders such as autism. In fact research on the use of humanoid robots to diagnose and treat autism is being conducted in the broader scope of Yale's humanoid robotics program.