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和重要。 该项目的重点是人形机器人，随着它们的复杂性的提高，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执行，并且因为它们使人类更容易与自动化进行交互。该项目特别关注如何对人形机器人进行编程;即如何尽可能简单有效地对它们的运动和交互进行编程。 重点不是开发机器人运动或传感的新算法。 更确切地说，一旦掌握了算法，如何编程机器人走路，挥动手臂，拍手或拿起物体？ 一个人如何以一种高层次的方式做到这一点，既没有不必要的细节，又有足够的表现力来捕捉所有想要的动作和互动？这项工作的核心是设计一种名为“Dance”的领域特定语言，这种语言高度抽象，易于使用，但具有足够的表达能力来描述各种有用的机器人动作。Dance融合了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。 例如，Dance使用基于事件的声明性反应，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（例如肢体之间的交互）和内部编程事件（计时器、远程消息、用户命令等）做出响应。 创新的语言研究使行为成为Dance中的计算对象，这使得程序能够抽象（聚合）动作序列并评估这些序列的交互。 该语言也服从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Dance程序的关键运行时属性。 这项工作还包括一个名为“Dance Studio”的编程环境，它能够模拟并可视化运行的Dance程序，使程序员能够在全面部署机器人之前动态调试程序。Dance语言研究开创了一种控制编程概念，适用于许多需要复杂的聚合系统行为或操作的应用，在这种情况下，这些行为必须得到协调和保证。 这项研究是耶鲁大学一项更广泛的议程的一部分，并支持该议程，即创造“社交能力强”的机器人。 构建一台能够识别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教师进行学习创造了可能性，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研究人类社会发展的许多方面的调查工具。 例如，能够感知地识别社交线索的机器人可以用于提供社交响应的定量度量。 这个指标可能是一个有用的诊断工具，为社会发展障碍，如自闭症。 事实上，关于使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.