Title
Ontology design for task allocation and management in urban search and rescue missions
Author
Saad, E.
Hindriks, K.V.
Neerincx, M.A.
Contributor
van den Herik, J. (editor)
Rocha, A.P. (editor)
Publication year
2018
Abstract
Task allocation and management is crucial for human-robot collaboration in Urban Search And Rescue response efforts. The job of a mission team leader in managing tasks becomes complicated when adding multiple and different types of robots to the team. Therefore, to effectively accomplish mission objectives, shared situation awareness and task management support are essential. In this paper, we design and evaluate an ontology which provides a common vocabulary between team members, both humans and robots. The ontology is used for facilitating data sharing and mission execution, and providing the required automated task management support. Relevant domain entities, tasks, and their relationships are modeled in an ontology based on vocabulary commonly used by firemen, and a user interface is designed to provide task tracking and monitoring. The ontology design and interface are deployed in a search and rescue system and its use is evaluated by firemen in a task allocation and management scenario. Results provide support that the proposed ontology (1) facilitates information sharing during missions; (2) assists the team leader in task allocation and management; and (3) provides automated support for managing an Urban Search and Rescue mission. Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved Institute for Systems and Technologies of Information, Control and Communication (INSTICC)
Subject
Human Robot Collaboration
Ontology
Rescue
Task Management
Urban Search
Artificial intelligence
Machine design
Ontology
Robots
User interfaces
Human-robot collaboration
Information sharing
Management scenarios
Rescue
Situation awareness
Task management
Urban search
Urban search and rescue
Human resource management
To reference this document use:
http://resolver.tudelft.nl/uuid:fd47d7ac-1df8-4630-ac86-178025af9e9d
TNO identifier
788782
Publisher
SciTePress
ISBN
9789897582752
Source
10th International Conference on Agents and Artificial Intelligence, ICAART 2018. 16 January 2018 through 18 January 2018, 622-629
Document type
conference paper