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As increasingly more research efforts are geared towards creating robots that can teach and interact with children in educational contexts, it has been speculated that endowing robots with artificial empathy may facilitate learning. In this paper, we provide a background to the concept of empathy, and how it factors into learning. We then present our approach to equipping a robotic tutor with several empathic qualities, describing the technical architecture and its components, a map-reading learning scenario developed for an interactive multitouch table, as well as the pedagogical and empathic strategies devised for the robot. We also describe the results of a pilot study comparing the robotic tutor with these empathic qualities against a version of the tutor without them. The pilot study was performed with 26 school children aged 10–11 at their school. Results revealed that children in the test condition indeed rated the robot as more empathic than children in the control condition. Moreover, we explored several related measures, such as relational status and learning effect, yet no other significant differences were found. We further discuss these results and provide insights into future directions.

We describe the Cataway (Catapult Segway), a Segway RMP-based mobile robotic platform which can autonomously throw a ball at a given target, intended to be used as a companion for a human beach ball player. The platform’s throwing mechanism and software architecture were designed, implemented and tested as part of a students’ lab course in practical mobile robotics. The concept allows students to gain practical experience with an actual mobile robot through a motivating scenario and a gentle learning curve. We present results of a simple, yet effective machine learning approach which allows the robot to learn to hit its target from any position.