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Cognition-enabled Framework for Mixed Human-Robot Rescue Teams

Fereshta Yazdani, Gayane Kazhoyan, Asil Kaan Bozcuoğlu, Andrei Haidu, Ferenc Bálint-Benczédi, Mihai Pomarlan, Michael Beetz

Year
2018
Citations
18

Abstract

With the advancements in robotic technology and the progress in human-robot interaction research, the interest in deploying mixed human-robot teams in rescue missions is increasing. Due to their complementary capabilities in terms of locomotion, visibility and reachability of areas, human-robot teams are considerably deployed in real-world settings, albeit the robotic agents in such scenarios are normally fully teleoperated. A major barrier to successful and efficient mission execution in those teams is the lack of cognitive skills in robotic systems. In this paper, we present a cognition-enabled framework and an implemented system where robotic agents are equipped with cognitive capabilities to naturally communicate with humans and autonomously perform tasks. The framework allows for natural tasking of robots, reasoning about robot behavior, capabilities and actions, and a common belief state representation for shared mission awareness of robots and human operators.

Keywords

RobotComputer scienceHuman–robot interactionHuman–computer interactionTeleoperationReachabilitySearch and rescueVisibilityCognitionArtificial intelligence

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