MD This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.

Robotic Development Environments (RDEs) have come to play an increasingly important role in robotics research in general, and for the development of architectures for mobile robots in particular. Yet, no systematic evaluation of available RDEs has been performed; establishing a comprehensive list of evaluation criteria targeted at robotics applications is desirable that can subsequently be used to compare their strengths and weaknesses. Moreover, there are no practical evaluations of the usability and impact of a large selection of RDEs that provides researchers with the information necessary to select an RDE most suited to their needs, nor identifies trends in RDE research that suggest directions for future RDE development. This survey addresses the above by selecting and describing nine open source, freely available RDEs for mobile robots, evaluating and comparing them from various points of view. First, based on previous work concerning agent systems, a conceptual framework of four broad categories is established, encompassing the characteristics and capabilities that an RDE supports. Then, a practical evaluation of RDE usability in designing, implementing, and executing robot architectures is presented. Finally, the impact of specific RDEs on the field of robotics is addressed by providing a list of published applications and research projects that give concrete examples of areas in which systems have been used. The comprehensive evaluation and comparison of the nine RDEs concludes with suggestions of how to use the results of this survey and a brief discussion of future trends in RDE design. 1

Military de-mining, mixed-initiative, collaborative workspace, adjustable autonomy, performance and evaluation This paper discusses experimental results achieved by using mixed initiative robot behavior to address the challenges of detecting and marking buried metal landmines. Mission requirements pertaining to communication bandwidth and operator workload precluded conventional approaches to communication and tasking. Instead, a framework for sharing control and communicating “behavior intent ” was developed to coordinate activities of intelligent unmanned air and ground vehicles. To alleviate dependence on global positioning, collaborative tasking tools were developed that use common reference points in the environment to correlate disparate internal representations (e.g. aerial imagery and ground-based occupancy grids). The behaviors allow each team member to act independently while communicating environmental features and task intent at a high level. Results show that the resulting system produced a significant decrease in task time to completion and a significant increase in detection accuracy and reliability when compared to the current military baseline. As required, the experiment was accomplished without dependence on global positioning or continuous network communication. These findings indicate that by providing an appropriate means to interleave human and robotic intent, mixed initiative behaviors can address complex and critical missions where neither teleoperated nor autonomous strategies have succeeded.

Abstract — Roboticists have frequently found that users are notoriously unwilling to pass control to autonomy, even when appropriate. It is important to find ways to promote the use of autonomy when switching out of manual mode is needed. This becomes important when autonomy is inherently better equipped to support the task at hand, especially when autonomy is safer than manual control. This paper proposes a selection of slightly subversive interaction design approaches that leverage knowledge about human behavior and may lead to greater utilization of autonomy by robot users. Keywords-component; human-robot interaction, autonomy, interaction design I.