With the Cellulo project , a part of the Transversal Educational Activities of the NCCR Robotics, we introduced a new robotic platform which is small and easily deployable. A dotted pattern printed on regular paper enables the Cellulo robots with absolute localization with a precision of 270 microns . The robots also have a new locomotion system with a drive relying on a permanent magnet to actuate coated metal balls . This new drive design allows backdrivability; i.e. it allows the robot to move and to be moved without damaging it. With this system, we also implemented a haptic feedback modality, allowing the user to feel forces when grasping the robot . The robots are connected via Bluetooth to a master (PC or tablet) that handles the logical and computation of the activity. The onboard PCB of the robots only allows for proceeding the localization (image capture and decoding of the pattern) and the control of the three wheels actuation. During two years, we developed several learning activities using the robots. The Figure for example shows the Feel the Wind activity, in which the learners were taught that the wind was formed by air moving from with high to low pressure points.
In the Cellulo project, we also started to explore the use of haptic feedback for learners. Haptic feedback enables us to render forces, but also borders, angles, or points. We developed a series of haptic capabilities and small interaction tasks that can be included in learning activities to inform the learner . We tested the haptic feedback with children for instance in the symmetry activity, in which the child is able to formulate hypothesis on the placement of the symmetrical shape and to verify their claims by feel haptically the shape on paper (left Figure). We also tested with some pilot with visually impaired children who were able to explore a map of their classroom using the Cellulo robots. Research Perspectives for Tangible Swarm Interaction and Haptic for Learners: We are now exploring the dynamics of the group of learners in manipulating the robots. The collaboration among learner is not always optimal, and a challenge would be to use the swarm robots to analyses and regulate the collaboration among learners. As these shared resource can be intelligent agents, they could rearrange themselves according to the collaborative state of the group.