Clarification dialogues in human-augmented mapping
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
Dynamic leadership for human-robot teams
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
Human control for cooperating robot teams
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Integrating Human Inputs with Autonomous Behaviors on an Intelligent Wheelchair Platform
IEEE Intelligent Systems
Hardware-assisted multiple object tracking for human-robot-interaction
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
Simulation of a teleautonomous multiple robot system with a single human operator
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Human-robot communication for collaborative decision making - A probabilistic approach
Robotics and Autonomous Systems
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We submit that the most interesting and fruitful human-robot 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 challengesinherent 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.