Query-based integration of heterogeneous knowledge bases for search and rescue tasks

Fereshta Yazdani (Corresponding author), Sebastian Blumenthal, Nico Huebel, Asil Kaan Bozcuoğlu, Michael Beetz, Herman Bruyninckx

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Uittreksel

Recently, advances in robotics’ technology and research focus on complex scenarios. In these scenarios, robots have to act and respond fast to situational demands. First, they require heterogeneous knowledge from various sources. Then, they need to integrate this knowledge with their reasoning methodologies. These reasoning methodologies are typically different for every domain. This paper introduces an integrated knowledge processing methodology. This methodology uses query mechanisms and model-to-model transformations. Combining these two mechanisms enables processing of heterogeneous knowledge bases. The methodology is demonstrated for an outdoor scenario with diverse systems. In this scenario knowledge and reasoning methods from various sources are integrated. This includes static knowledge from. Open Sreet Map and Digital Elevation Models. The Robot Scene Graph tracks changes in the world and provides geometric reasoning. KnowRob with its SHERPA ontology and OPENEASE provide further reasoning capabilities.

TaalEngels
Pagina's80-91
Aantal pagina's12
TijdschriftRobotics and Autonomous Systems
Volume117
DOI's
StatusGepubliceerd - 1 jul 2019

Vingerafdruk

Knowledge Base
Query
Reasoning
Methodology
Scenarios
Robots
Processing
Robot
Geometric Reasoning
Ontology
Open Map
Robotics
Digital Elevation Model
Model Transformation
Integrate
Knowledge
Graph in graph theory

Trefwoorden

    Citeer dit

    Yazdani, Fereshta ; Blumenthal, Sebastian ; Huebel, Nico ; Bozcuoğlu, Asil Kaan ; Beetz, Michael ; Bruyninckx, Herman. / Query-based integration of heterogeneous knowledge bases for search and rescue tasks. In: Robotics and Autonomous Systems. 2019 ; Vol. 117. blz. 80-91
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    abstract = "Recently, advances in robotics’ technology and research focus on complex scenarios. In these scenarios, robots have to act and respond fast to situational demands. First, they require heterogeneous knowledge from various sources. Then, they need to integrate this knowledge with their reasoning methodologies. These reasoning methodologies are typically different for every domain. This paper introduces an integrated knowledge processing methodology. This methodology uses query mechanisms and model-to-model transformations. Combining these two mechanisms enables processing of heterogeneous knowledge bases. The methodology is demonstrated for an outdoor scenario with diverse systems. In this scenario knowledge and reasoning methods from various sources are integrated. This includes static knowledge from. Open Sreet Map and Digital Elevation Models. The Robot Scene Graph tracks changes in the world and provides geometric reasoning. KnowRob with its SHERPA ontology and OPENEASE provide further reasoning capabilities.",
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    Query-based integration of heterogeneous knowledge bases for search and rescue tasks. / Yazdani, Fereshta (Corresponding author); Blumenthal, Sebastian; Huebel, Nico; Bozcuoğlu, Asil Kaan; Beetz, Michael; Bruyninckx, Herman.

    In: Robotics and Autonomous Systems, Vol. 117, 01.07.2019, blz. 80-91.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

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    Yazdani F, Blumenthal S, Huebel N, Bozcuoğlu AK, Beetz M, Bruyninckx H. Query-based integration of heterogeneous knowledge bases for search and rescue tasks. Robotics and Autonomous Systems. 2019 jul 1;117:80-91. Beschikbaar vanaf, DOI: 10.1016/j.robot.2019.03.013