Electrically tunable lenses are conceived as deformable adaptive optical components able to change focus without motor-controlled translations of stiff lenses. In order to achieve large tuning ranges, large deformations are needed. This requires new technologies for the actuation of highly stretchable lenses. This paper presents a configuration to obtain compact tunable lenses entirely made of soft solid matter (elastomers). This was achieved by combining the advantages of dielectric elastomer actuation (DEA) with a design inspired by the accommodation of reptiles and birds. An annular DEA was used to radially deform a central solid-body lens. Using an acrylic elastomer membrane, a silicone lens and a simple fabrication method, we assembled a tunable lens capable of focal length variations up to 55%, driven by an actuator four times larger than the lens. As compared to DEA-based liquid lenses, the novel architecture halves the required driving voltages, simplifies the fabrication process and allows for a higher versatility in design. These new lenses might find application in systems requiring large variations of focus with low power consumption, silent operation, low weight, shock tolerance, minimized axial encumbrance and minimized changes of performance against vibrations and variations in temperature.

Robot's perception is essential for performing highlevel tasks such as understanding, learning, and in general, human-robot interaction (HRI). For this reason, different perception systems have been proposed for different robotic platforms in order to detect high-level features such as facial expressions and body gestures. However, due to the variety of robotics software architectures and hardware platforms, these highly customized solutions are hardly interchangeable and adaptable to different HRI contexts. In addition, most of the developed systems have one issue in common: they detect features without awareness of the real-world contexts (e.g., detection of environmental sound assuming that it belongs to a person who is speaking, or treating a face printed on a sheet of paper as belonging to a real subject). This paper presents a novel social perception system (SPS) that has been designed to address the previous issues. SPS is an outof-the-box system that can be integrated into different robotic platforms irrespective of hardware and software specifications. SPS detects, tracks and delivers in real-time to robots, a wide range of human-and environment-relevant features with the awareness of their real-world contexts. We tested SPS in a typical scenario of HRI for the following purposes: to demonstrate the system capability in detecting several high-level perceptual features as well as to test the system capability to be integrated into different robotics platforms. Results show the promising capability of the system in perceiving real world in different social robotics platforms, as tested in two humanoid robots i.e., FACE and ZENO.

Abstract. This paper presents the EU EASEL project, which explores the potential impact and relevance of a robot in educational settings. We present the project objectives and the theorectical background on which the project builds, briefly introduce the EASEL technological developments, and end with a summary of what we have learned from the evaluation studies carried out in the project so far.