Presence: Teleoperators and Virtual Environments - Virtual environments: Virtual environments and mobile robots: Control, simulation, and robot pilot training
The first segway soccer experience: towards peer-to-peer human-robot teams
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
General Model of Human-Robot Cooperation Using a Novel Velocity Based Variable Impedance Control
WHC '07 Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
Skill acquisition and use for a dynamically-balancing soccer robot
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Human and robot perception in large-scale learning from demonstration
Proceedings of the 6th international conference on Human-robot interaction
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Many robotic applications feature a mixture of interacting teleoperated and autonomous robots. In several such domains, human operators must make decisions using very limited perceptual information, e.g. by viewing only the noisy camera feed of their robot. There are many interaction scenarios where such restricted visibility impacts teleoperation performance, and where the role of autonomous robots needs to be reinforced. In this paper, we report on an experimental study assessing the effects of limited perception on human decision making, in interactions between autonomous and teleoperated NAO robots, where subjects do not have prior knowledge of how other agents will respond to their decisions. We evaluate the performance of several subjects under varying perceptual constraints in two scenarios; a simple cooperative task requiring collaboration with an autonomous robot, and a more demanding adversarial task, where an autonomous robot is actively trying to outperform the human. Our results indicate that limited perception has minimal impact on user performance when the task is simple. By contrast, when the other agent becomes more strategic, restricted visibility has an adverse effect on most subjects, with the performance level even falling below that achieved by an autonomous robot with identical restrictions. Our results could inform decisions about the division of control between humans and robots in mixed-initiative systems, and in determining when autonomous robots should intervene to assist operators.