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.

Remote characterization of high radiation environments is a pressing application area where robots can provide benefits in terms of time, cost, safety and quality of data. However, the DOE roadmap for Robotics and Intelligent Machines states that 'usability' may well prove to be the most challenging and yet crucial component of robotic systems for remote characterization and handling of radioactive and hazardous materials. In 2001, the INEEL successfully deployed a teleoperated robotic system coupled with a Gamma Locating and Isotopic Identification Device (RGL&IID) to characterize an area that had been closed to human entry for many years. This paper examines the human-robot dynamic of this teleoperated task and the limitations inherent to the master-slave strategy employed. Next, the paper outlines an innovative, mixed-initiative command and control architecture developed to address these limitations. The resulting, mixed-initiative control architecture retains the human in the loop, but interleaves multiple levels of human intervention into the functioning of a robotic system that can, in turn, scale its own level of initiative to meet whatever level of input is handed down.

Micro-robots will soon be available for deployment by the thousands. Consequently, controlling and coordinating a force this large to accomplish a prescribed task is of great interest. This paper describes a flexible architecture for modeling thousands of autonomous agents simultaneously. The agents' behavior is based on a subsumption architecture in which individual behaviors are prioritized with respect to all others. The primary behavior explored in this work is a group formation behavior based on social potential fields (Reif and Wang 1999). This paper extends the social potential field model by introducing a neutral zone within which other behaviors may exhibit themselves. Previous work with social potential fields has been restricted to models of "perfect" autonomous agents. The paper evaluates the effect of social potential fields in the presence of agent death (failure) and imperfect sensory input.

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Small-sized and micro-robots will soon be available for deployment in large-scale forces. Consequently, the ability of a human operator to coordinate and interact with largescale robotic forces is of great interest. This paper describes the ways in which modeling and simulation have been used to explore new possibilities for human-robot interaction. The paper also discusses how these explorations have fed implementation of a unified set of command and control concepts for robotic force deployment. Modeling and simulation can play a major role in fielding robot teams in actual missions. While live testing is preferred, limitations in terms of technology, cost, and time often prohibit extensive experimentation with physical multi-robot systems. Simulation provides insight, focuses efforts, eliminates large areas of the possible solution space, and increases the quality of actual testing.