The Robot Show Must Go On: Effective Responses to Robot Failures This paper consists of a failure analysis of two robot performance productions. Both productions included threeweek rehearsal periods, and culminated in live performances including both robots and humans. To develop these productions, a theater artist collaborated with a robotics lab to develop, (1) a narrative dance performed live on stage and (2) an improvisational performance in a public space. While the interdisciplinary team did not set out to explore robot failures, failures played an everpresent role during the eighteen rehearsals and two live performances. This paper details strategies for addressing, planning for, and rehearsing responses to robot failures on stage, both technical and choreographic. In addition to scaffolding future robot theater performances, we discuss how these strategies apply to other customer and audiencefacing robots, including sponsor demos. The onstage exploration of robot chairs and human performers also suggests that humans can conceptualize minimal robots as both characters and props, moving fluidly from one to the other. We hope these strategies ensure that future audiences will want the robot shows to go on, as well as expand ideas about the types of robots that can be cast in future humanrobot productions.

Generation of expressive motions for a tabletop robot interpolating from handmade animations Motion is an important modality for humanrobot interaction. Besides a fundamental component to carry out tasks, through motion a robot can express intentions and expressions as well. In this paper, we focus on a tabletop robot in which motion, among other modalities, is used to convey expressions. The robot incorporates a set of preprogrammed motion animations that show different expressions with various intensities. These have been created by designers with expertise in animation. The objective in the paper is to analyze if these examples can be used as demonstrations, and combined by the robot to generate additional richer expressions. Challenges are the representation space used, and the scarce number of examples. The paper compares three different learning from demonstration approaches for the task at hand. A user study is presented to evaluate the resultant new expressive motions automatically generated by combining previous demonstrations.