Cognition-enabled Framework for Mixed Human-Robot Rescue Teams

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.

Authors

• Fereshta Yazdani
• Gayane Kazhoyan
• Asil Kaan Bozcuoglu
• Andrei Haidu
• Ferenc Balint-Benczedi
• Daniel Beßler
• Mihai Pomarlan
• Michael Beetz

Keywords

• Cognition
• Robot sensing systems
• Geographic information systems
• Task analysis
• Lakes
• Bridges
• Rescue Teams
• Robotic System
• Human Operator
• Human-robot Interaction
• Cognitive Capabilities
• Robotic Technology
• Successful Execution
• Belief State
• Rescue Missions
• Robotic Agents
• Complementary Capabilities
• Source Of Information
• Knowledge Base
• Executive Function
• Natural Language
• Spatial Relationship
• Geographic Information System
• Episodic Memory
• Team Sports
• Perceptual System
• Robot Operating System
• Semantic Map
• Unreal Engine
• Different Sources Of Information
• Robot Control
• Linguistic Constructions
• Simulated Robot
• Robotics Research
• Evaluation Scenarios
• Robotic Platform