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.
