Cognitive Robotics: A Curriculum for Machines that See and Manipulate their World

认知机器人：为机器观察和操纵世界的课程

• 批准号: 0717705
• 负责人: David Touretzky
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0717705&HistoricalAwards=false
• 关键词: Cognitive; Robotics; Curriculum; Machines; See

Computer Science (31)This project is extending the Tekkotsu open source robot programming framework developed in the PI's lab (see Tekkotsu.org) by creating new primitives for manipulation and for control of posture and balance, and by further enriching the existing repertoire of primitives for vision processing, mapping, and navigation. It also is providing the first systematic study of how a higher level approach to robot programming influences educational outcomes. This project is developing software and course materials that foster a new, higher-level approach to introductory robotics for undergraduates, called "cognitive robotics." Cognitive robotics courses are already offered at Carnegie Mellon, Spelman College, and several other schools with which the PI is collaborating. The project is promoting the wider adoption of cognitive robotics curricula by offering workshops at Carnegie Mellon for computer science educators, making presentations at conferences such as SIGCSE and AAAI, disseminating open source software and educational materials via the web, and creating a cognitive robotics textbook.Until recently, undergraduate robotics courses have been limited by inexpensive platforms which provide only meager sensors and minimal processing power. Such courses have therefore tended to focus on mechanical construction activities and programming simple reactive behaviors such as wall following. While some platforms provide for an optional video camera, image processing support has typically been limited to crude blob detection, not true computer vision. In cognitive robotics, students use more sophisticated robots that can see and recognize objects, physically manipulate them, build a map of the environment, and navigate on that map. The Sony AIBO robot dog was the first platform suitable for this approach, but other capable platforms are now becoming available. Undergraduates can be taught to program these robots using high-level primitives that draw inspiration from ideas in cognitive science. This allows even beginning roboticists to explore interesting problems in perception and manipulation while the complexities of advanced image processing and motor control are taken care of for them.

这个项目扩展了PI实验室开发的tekkotsuu开源机器人编程框架（见Tekkotsu.org），通过创建用于操作和控制姿态和平衡的新基元，并进一步丰富了用于视觉处理、映射和导航的现有基元库。它还提供了第一个系统的研究，研究更高层次的机器人编程方法如何影响教育成果。这个项目正在开发软件和课程材料，为本科生提供一种新的、更高层次的机器人入门方法，称为“认知机器人”。认知机器人课程已经在卡耐基梅隆大学、斯佩尔曼学院和其他几所PI正在合作的学校开设。该项目通过在卡内基梅隆大学为计算机科学教育者提供研讨会，在SIGCSE和AAAI等会议上发表演讲，通过网络传播开源软件和教育材料，以及创建认知机器人教科书，促进认知机器人课程的广泛采用。直到最近，本科机器人课程还受到廉价平台的限制，这些平台只能提供简陋的传感器和最低限度的处理能力。因此，这类课程往往侧重于机械施工活动和编程简单的反应性行为，如跟着墙走。虽然有些平台提供了可选的视频摄像头，但图像处理支持通常仅限于粗糙的斑点检测，而不是真正的计算机视觉。在认知机器人中，学生们使用更复杂的机器人，这些机器人可以看到和识别物体，对它们进行物理操作，构建环境地图，并在地图上导航。索尼AIBO机器狗是第一个适合这种方法的平台，但其他有能力的平台现在也开始可用。本科生可以被教导使用高级原语来编程这些机器人，这些原语可以从认知科学的思想中汲取灵感。这使得即使是刚开始的机器人专家也可以探索感知和操纵方面的有趣问题，同时先进的图像处理和运动控制的复杂性也得到了照顾。