A flexible sensor technology for the distributed measurement of interaction pressure

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted

Trajectory Deformations from Physical Human-Robot Interaction

Robots are finding new applications where physical interaction with a human is necessary: manufacturing, healthcare, and social tasks. Accordingly, the field of physical human-robot interaction (pHRI) has leveraged impedance control approaches, which support compliant interactions between human and robot. However, a limitation of traditional impedance control is that---despite provisions for the human to modify the robot's current trajectory---the human cannot affect the robot's future desired trajectory through pHRI. In this paper, we present an algorithm for physically interactive trajectory deformations which, when combined with impedance control, allows the human to modulate both the actual and desired trajectories of the robot. Unlike related works, our method explicitly deforms the future desired trajectory based on forces applied during pHRI, but does not require constant human guidance. We present our approach and verify that this method is compatible with traditional impedance control. Next, we use constrained optimization to derive the deformation shape. Finally, we describe an algorithm for real time implementation, and perform simulations to test the arbitration parameters. Experimental results demonstrate reduction in the human's effort and improvement in the movement quality when compared to pHRI with impedance control alone

Micro-timing of backchannels in human-robot interaction

Inden B, Malisz Z, Wagner P, Wachsmuth I. Micro-timing of backchannels in human-robot interaction. Presented at the Timing in Human-Robot Interaction: Workshop in Conjunction with the 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI2014), Bielefeld, Germany

How humans behave and evaluate a social robot in real-environment settings

Behavioral analysis has proven to be an important method to study human-robot interaction in real-life environments providing highly relevant insights for developing new theoretical and practical models of appropriate social robot design. In this paper we describe our approach to study human-robot interaction by combining human behavioral analysis with robot evaluation results. The approach is exemplified by a case study performed with a social robot receptionist in real-life settings. Our preliminary results are encouraging, as many behavior categories could be successfully related to certain evaluation patterns. With our analysis we hope to add a useful contribution to social-robotic design concerning user modeling issues and evaluation predictions