This is funding to support preliminary work related to the study of human-robot interaction (HRI) in safety-critical situations, such as urban search and rescue. The hope is that by bringing together researchers in HCI and Robotics, it will be possible for the PIs to perform well-designed and rigorous studies of HRI unlike any work that has been done in the past. The PIs will focus on the effectiveness of techniques for making human operators aware of pertinent information regarding the robot and its environment. By studying the best practices in HRI, they will enable the creation of better interfaces that provide decision support and reduce the workload of the operator. The PIs will validate their findings by creating new interfaces for safety-critical robot systems. They will also develop methods for testing and evaluating human-robot interaction, which will result in better metrics, and will further develop best practices and design guidelines for HRI in safety-critical applications, validated through the testing of new and revised interfaces. It is important to understand how to turn sensor data into information for decision support to reduce the workload of the human operator and the potential for error, even when the robot and its operator are physically separated.
Broader Impacts: The results of this work will allow the PIs to develop course modules for the Robotics II (undergraduate/graduate) and Evaluation of Human-Computer Interaction (graduate) courses at the University of Massachusetts, Lowell. The research will be disseminated through conference and journal articles; collected data will be made available to interested researchers. All participants in the study will receive copies of the evaluations of their systems, and will have the opportunity to discuss the results with the PIs; it is expected that these systems will improve due to this feedback, and participants will be encouraged to participate in a future study phase to evaluate the revised interfaces. More generally, improving human-robot interaction will benefit society as a whole; for example, the results will be useful to the creation of better robotic systems for assistive technology and for search and rescue.
