The drive for increasing adoption of HRI technolo-gies is evident through research and development of manufac-turing, social, medical, and service robot solutions. However, novel methods and metrics are required to overcome the barrier between fundamental HRI research and its adoption in real-world environments. Hence, the fourth installment of the annual workshop, 'Test Methods and Metrics for Effective HRI,’ seeks to identify novel and emerging test methods and metrics for the holistic assessment and assurance of HRI performance. Specifically, the focus is on identifying innovative methods for the evaluation of HRI performance and to advance the growth of the HRI community based on the principles of collaboration, data sharing, and repeatability. The goal of this workshop is to break the boundaries between the development and adoption of HRI technologies through the promotion of robust experimental design, test methods, and metrics for assessing interaction and interface designs. This workshop will have participants from var-ious sectors in the HRI research community including academia, industry, and government in order to accomplish its aims.

In this paper, we present sensor-controlled antagonistic pneumatic actuators (SCAPAs) that integrate proven soft robotic actuators and sensors into a simplified, controllable design. The antagonistic actuators together compose a bidirectional bending actuator with embedded capacitive strain sensors. By designing the SCAPAs from the ground-up for closed-loop control, we are able to minimize both the number of constituent components and the types of materials used, and further streamline the manufacturing processes. These improvements are embodied in the multipurpose use of a single conductive fabric sheet for both actuation and sensing, integrated into an otherwise all-silicone device. Such reduced material complexity allows us to use simple finite element analysis (FEA) models to predict the performance of a given design. We compare various designs to maximize sensor effectiveness using FEA and experimentally verify the suitability of select designs for state reconstruction. After converging on our final design, we demonstrate that this design evaluation process enables the use of simple control strategies to achieve closed-loop control.

Materials with variable stiffness have the potential to provide a range of new functionalities, including system reconfiguration by tuning the location of rigid links and joints. In particular, wearable applications would benefit from variable stiffness materials in the context of active braces that may stiffen when necessary and soften when mobility is required. In this work, we present fibers capable of adjusting to provide variable stiffness in wearable fabrics. The variable stiffness fibers are made from shape memory materials, where shape memory alloy (SMA) is coated with a thin film of shape memory polymer (SMP). The fibers, which are fabricated via a continuous feed-through process, reduce in bending stiffness by an order of magnitude when the SMP goes through the glass transition. The transition between rubbery and glassy state is accomplished by direct joule heating of the embedded SMA wire. We employ a COMSOL model to relate the current input to the time required for the fibers to transition between stiffness states. Finally, we demonstrate how this device can be worn and act as a joint stability brace on human fingers.

Future generations of wearable robots will include systems constructed from conformable materials that do not constrain the natural motions of the wearer. Fabrics represent a class of highly conformable materials that have the potential for embedded function and are highly integrated into our daily lives. In this work, we present a robotic fabric with embedded actuation and sensing. Attaching the same robotic fabric to a soft body in different ways leads to unique motions and sensor modalities with many different applications for robotics. In one mode, the robotic fabric acts around the circumference of the body, and compression of the body is achieved. Attaching the robotic fabric in another way, along one surface of a body for example, bending is achieved. We use thread-like actuators and sensors to functionalize fabric via a standard textile manufacturing process (sewing). The actuated fabric presented herein yields a contractile force of 9.6N and changes in length by approximately 60% when unconstrained. The integrated strain sensor is evaluated and found to have an RMS error of 14.6%, and qualitatively differentiates between the compressive and bending motions demonstrated.