As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human beings as animate elements of their environment. The interpretation by this human counterpart is critical to the success of the system's integration: "knobs" on the system need to make sense to a human counterpart; an artificial agent should have a way of notifying a human counterpart of a change in system state, possibly through motion profiles; and the motion of a human counterpart may have important contextual clues for task completion. Thus, professional choreographers, dance practitioners, and movement analysts are critical to research in robotics. They have design methods for movement that align with human audience perception; they can help identify simplified features of movement that will effectively accomplish human-robot interaction goals; and they have detailed knowledge of the capacity of human movement. This article provides approaches employed by one research lab, specific impacts on technical and artistic projects within, and principles that may guide future such work. The background section reports on choreography, somatic perspectives, improvisation, the Laban/Bartenieff Movement System, and robotics. From this context methods including embodied exercises, writing prompts, and community building activities have been developed to facilitate interdisciplinary research. The results of this work are presented as an overview of a smattering of projects in areas like high-level motion planning, software development for rapid prototyping of movement, artistic output, and user studies that help understand how people interpret movement. Finally, guiding principles for other groups to adopt are posited.

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Live performance is a vehicle where theatrical devices are used to exemplify, probe, or question how humans think about objects, each other, and themselves. This paper presents work using this vehicle to explore human perceptions of robot and human capabilities. The paper documents four performances at three distinct venues where user studies were conducted in parallel to live performance. A set of best practices for successful collection of data in this manner over the course of these trials is developed. Then, results of the studies are presented, giving insight into human opinions of a variety of natural and artificial systems. In particular, participants are asked to rate the expressivity of 12 distinct systems, displayed on stage, as well as themselves. The results show trends ranking objects lowest, then robots, then humans, then self, highest. Moreover, objects involved in the show were generally rated higher after the performance. Qualitative responses give further insight into how viewers experienced watching human performers alongside elements of technology. This work lays a framework for measuring human perceptions of robotic systems – and factors that influence this perception – inside live performance and suggests black-that through the lens of expressivity systems of similar type are rated similarly by audience members.