Enhancing Robot Programming with Visual Feedback and Augmented Reality

Abstract

In our previous research, we showed that students using the educational robot Thymio and its visual programming environment were able to learn the important computer-science concept of event-handling. This paper extends that work by integrating augmented reality ( ar) into the activities. Students used a tablet that displays in real time the event executed on the robot. The event is overlaid on the tablet over the image from a camera, which shows the location of the robot when the event was executed. In addition, visual feedback (fb) was implemented in the software. We developed a novel video questionnaire to investigate the performance of the students on robotics tasks. Data were collected comparing four groups: ar+fb, ar+non-fb, non-ar+fb, non-ar+non-fb. The results showed that students receiving feedback made significantly fewer errors on the tasks. Those using ar made fewer errors, but this improvement was not significant, although their performance improved. Technical problems with the ar hardware and software showed where improvements are needed.

Bringing Robotics to Formal Education: The Thymio Open-Source Hardware Robot

“…The IDE integrates real-time feedback of the status of program execution, as this feature was recognized of critical importance to properly learn programming [21]. This capability is provided both with the VPL [22] and in the scripting environment, by displaying the content of variables in real time through texts or plots. The IDE also provides a help documentation 12 .…”

Pedagogical Uses of Thymio II: How Do Teachers Perceive Educational Robots in Formal Education?

“…The main criticism to date is that Thymio is incompatible with Scratch, the most common programming interface among beginners; however, this issue is very close to being resolved. Thanks to these factors, Thymio is gaining popularity in schools, and efforts are ongoing to improve it by including a wireless module and the use of augmented reality in the programming interface [16].…”

Debugging Quadrocopter Trajectories in Mixed Reality

“…Hereby, the simplification of debugging, the elimination of safety risks, and the easier development of swarm behavior by complementing physically existing robots with simulated ones were named as outstanding advantages. Furthermore, a study for the programming of a small two-wheeled robot [16] revealed no impact on the learning performance when using Augmented Reality (AR). The debugging of quadrocopters with a fixed camera in combination with LEDs is presented by [11].…”