Over the last few months the Plymouth Node of ALIZ-E has been working hard toward a rather large experiment that got underway at the start of the week. Last month we went to the Natural History Museum to showcase some of Plymouth University’s robotics research for Universities Week. That was used as a chance to give our system a hard beta test, which generally went very well. We identified some things that needed to be changed and made more robust, but all in all, we were very happy with the outcome.
After two weeks more development and ironing out creases in the code, we finally deployed our two systems to a local Plymouth Primary school on Monday morning this week and it will stay in two different classrooms for two weeks. You can see the setup below.
So, the system consists of a 27 inch all in one touch screen computer which essentially provides a shared input/malleable space for both the human and the robot. The Nao stands/kneels on one side of the screen, while the human is located on the other side, facing the robot. Behind the Nao is a Kinect sensor that is facing the human and can see just over the top of the Nao’s head.
Basically, on the touchscreen we run some programs that allow the children to play a non-competitive game with the robot. This is a categorisation task, where icons on screen (e.g. numbers, planets, colours) have to be moved into a particular location on the screen in order to be categorized in some way (e.g. odd or even number, numbers that are/not part of the 4 timetable, planets with moons and without moons). By keeping the basic underlying task simple, it is easy to change the icons and the categories to produce a wide repertoire of different games that are easily accessible for young children. As part of this game experience/setup, each child in the class has their own “saved account” (which they select by selecting their name on screen when prompted by the robot) which allows the robot to track their progress through the various games, and in turn pitch the level of difficultly accordingly. The robot also takes part in this game by also, moving icons onscreen, and as it is very open ended, turn taking tends to emerge from the process naturally as a result.
The rational for using a touchscreen is that is provides an interactive medium which is simultaneously intuitive for the human and the robot. In essence, the human is able to manipulate objects on screen in both a natural manner (say select them, drag and drop, ect) as well as being able to use similar cues as may be used with tables and such devices (e.g. swipe, pinch to zoom, ect). On the part of the robot, the touchscreen is a computer, makes communication between it and the robot very simple. Further more, when you present something on screen, the robot is able to gain lots of knowledge about objects that are being manipulated (and how) that may otherwise have been very difficult to obtain in the physical world. By providing a shared, malleable space that is virtual rather than physical, you overcome many of the limitations in both the Nao’s ability to manipulate real objects, as well as its perception limitations.
We use a Kinect for a similar reason. The Kinect is used to estimate head pose, and thus determine whether the human is looking at the screen, at the human, or somewhere else. This allows us to, in part, drive the gaze behaviour of the robot. For example, if the human is looking at the screen, then the robot can establish joint attention by doing the same, or if the human is looking at the robot then the robot knows that it can make eye contact. It is useful to have the Kinect act as a “fly in the corner” because some of these issues are difficult to achieve using the built in cameras on the Nao, particularly as they move as the head gazes around.
We’re keeping our fingers crossed that we aren’t bitten too hard by the “Demo Effect” (which means that as soon as it comes to actually showing a system working to real people, a fully working system in the lab decides to have a catastrophic break down…). Doubtless that we will seek to publish our results from the experiment in due course (so sorry for not detailing the experiment itself here), so watch this space… 😉