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We submit that the most interesting and fruitful humanrobot interaction (HRI) may be possible when the robot is able to interact with the human as a true team member, rather than a tool. However, the benefits of shared control can all too easily be overshadowed by challenges inherent to blending human and robot initiative. The most important requirements for peer-peer interaction are system trust and ability to predict system behavior. The human must be able to understand the reason for and effects of robot initiative. These requirements can only be met through careful application of human factors principles and usability testing to determine how users will interact with the system. This paper discusses the recent human participant usability testing, which took our current implementation to task using a search and rescue scenario within a complex, real-world environment. The purpose of testing was to examine how human operators work with the robotic system at each level of autonomy, and how interaction with the robot should be structured to enable situation awareness and task completion. Analyses revealed that our architecture equally supported situation awareness and target detection by novices and experts, although experienced users were more likely to have more performance expectations of the interface. Results also had implications regarding the ability of participants to effectively utilize the collaborative workspace and, most importantly, their ability to understand and willingness to accept robot initiative.

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This paper describes two steps in the evolution of human-robot interaction designs developed by the University of Massachusetts Lowell (UML) and the Idaho National Laboratory (INL) to support urban search and rescue tasks. We conducted usability tests to compare the two interfaces, one of which emphasized three-dimensional mapping while the other design emphasized the video feed. We found that participants desired a combination of the interface design approaches. As a result, we changed the UML system to augment its heavy emphasis on video with a map view of the area immediately around the robot. We tested the changes in a follow-on user study and the results from that experiment suggest that performance, as measured by the number of collisions with objects in the environment and time on task, is better with the new interaction techniques. Throughout the paper, we describe how we applied human-computer interaction principles and techniques to benefit the evolution of the human-robot interaction designs. While the design work is situated in the urban search and rescue domain, we feel the results can be generalized to domains that involve other search or monitoring tasks using remotely located robots.2

In order to apply mobile robots to a new range of applications, we require control architectures and interfaces that support symbiotic interaction. Remote deployment of mobile robots offers one of the most compelling opportunities to merge human intelligence with machine proficiency. This paper discusses a mixedinitiative control strategy based not on video, but on an abstracted, collaborative workspace-a 3-D, video-game representation constructed on-the-fly-that promotes situation-awareness and efficient tasking. The new interface requires orders of magnitude less bandwidth than teleoperation and permits transmission ranges of thousands of miles. Unlike video, which offers only a 1 st person, local environment perspective, the 3-D interface changes perspective to support changing levels of operator involvement and robot autonomy. The humanparticipant study presented evaluates the effectiveness of this interaction substrate on a remote exploration task. Results indicate that this new tool for interfacing humans and intelligent robots can reduce human error, support changing levels of human workload, promote human trust, and enable a spectrum of remote robotic applications which have never before been possible.