In designing and evaluating human-robot interactions and interfaces, researchers often use a simulated robot due to the high cost of robots and time required to program them. However, it is important to consider how interaction with a simulated robot differs from a real robot; that is, do simulated robots provide authentic interaction? We contribute to a growing body of work that explores this question and maps out simulated-versus-real differences, by explicitly investigating empathy: how people empathize with a physical or simulated robot when something bad happens to it. Our results suggest that people may empathize more with a physical robot than a simulated one, a finding that has important implications on the generalizability and applicability of simulated HRI work. Empathy is particularly relevant to social HRI and is integral to, for example, companion and care robots. Our contribution additionally includes an original and reproducible HRI experimental design to induce empathy toward robots in laboratory settings, and an experimentally validated empathy-measuring instrument from psychology for use with HRI.

The issue of believability is core to android science, the challenge of creating a robot that can pass as a near human. While researchers are making great strides in improving the quality of androids and their likeness to people, it is simultaneously important to develop theoretical foundations behind believability, and experimental methods for exploring believability. In this paper, we explore a visual processing approach to investigating the believability of android faces, and present results from a study comparing current-generation android faces to humans' faces. We show how android faces are still not quite as believable as humans, and provide some mechanisms that may be used to investigate and compare believability in future projects.

Remote control robots are being found in an increasing number of application domains, including search and rescue, exploration, and reconnaissance. There is a large body of HRI research that investigates interface design for remote navigation, control, and sensor monitoring, while aiming for interface enhancements that benefit the remote operator such as improving ease of use, reducing operator mental load, and maximizing awareness of a robot's state and remote environment. Even though many remote control robots have multi-degree-of-freedom robotic manipulator arms for interacting with the environment, there is only limited research into easy-to-use remote control interfaces for such manipulators, and many commercial robotic products are still using simplistic interface technologies such as keypads or gamepads with arbitrary mappings to arm morphology. In this paper, we present an original interface for the remote control of a multi-degree of freedom robotic arm. We conducted a controlled experiment to compare our interface to an existing commercial keypad interface and detail our results that indicate our interface was easier to use, required less cognitive task load, and enabled people to complete tasks more quickly. In this paper, we present an original interface for the remote control of a multi-degree of freedom robotic arm. We conducted a controlled experiment to compare our interface to an existing commercial keypad interface and detail our results that indicate our interface was easier to use, required less cognitive task load, and enabled people to complete tasks more quickly.