In this work, we introduce a biomorphic soft robotic skin for a hexapod robot platform and a Central Pattern Generator (CPG) based neural controller to generate respiratory-like motions on the skin. The design enables visio-haptic nonverbal communication between humans and robots and improves the robot’s aesthetics by enhancing its biomorphic qualities. We investigated if the soft robotic skin could increase user ratings of the robot’s warmth (RoSAS) and reported trust levels during interaction (MDMT). Contrary to our expectations and earlier findings, we did not find any increase in neither warmth nor trust from adding the soft robotic part. Furthermore, comments received from study participants indicate that trust in the robot is influenced by multiple factors, including appearance, movements, haptic qualities, and contextual factors. Based on our results, we propose directions for further research on pneumatically actuated soft robotic skins as means for nonverbal communication in human-robot interaction.

The position paper presents an argument that aesthetic theory and practice are pertinent to the rapidly expanding field of soft robotics. Soft robotics as an aesthetic phenomenon is introduced and contextualized drawing on the author's own research and practice. The potential of aesthetic perspectives and approaches in developing and implementing soft robotics are highlighted with a focus on technical design and human-robot interaction.

In this study, we examine whether touching a soft robot while doing different tasks can make participants synchronize their breathing rhythm with the robot. 28 participants interacted with the robot, which either was inflated and deflated, thus simulating breathing, or remained inactive. During the experiment, data were collected through two breathing belts and an EEG device. The findings of the study suggest higher arousal associated with positive emotional valence for participants in the breathing robot condition compared to the inactive robot condition. The participants in the breathing robot condition also breathed more deeply and regularly and blinked fewer times, a finding that suggests lower stress levels in comparison with people who interacted with the inactive robot. The analysis of the data suggests that touching the breathing robot led to some degrees of stress reduction, yet without leading to synchronization with the robot's inhalation rhythm.

Soft robotics is a growing field of research and one of its challenges is how to efficiently design a controller for a soft morphology. This paper presents a marine soft robot inspired by the ghost knifefish that swims on the water surface by using an undulating fin underneath its body. We investigate how propagating wave functions can be evolved and how these affect the swimming performance of the robot. The fin and body of the robot are constructed from silicone and six wooden fin rays actuated by servo motors. In order to bypass the reality gap, which would necessitate a complex simulation of the fish, we implemented a Covariance Matrix Adaptation Evolution Strategy (CMA-ES) directly on the physical robot to optimize its controller for travel speed. Our results show that evolving a simple sine wave or a Fourier series can generate controllers that outperform a hand programmed controller. The results additionally demonstrate that the best evolved controllers share similarities with the undulation patterns of actual knifefish. Based on these results we suggest that evolution on physical robots is promising for future application in optimizing behaviors of soft robots.