An ontology-based approach to improve the accessibility of ROS-based robotic systems
Tiddi, Ilaria Bastianelli, Emanuele Bardaro, Gianluca d’Aquin, Mathieu Motta, Enrico
Tiddi, Ilaria
Bastianelli, Emanuele
Bardaro, Gianluca
d’Aquin, Mathieu
Motta, Enrico
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Repository DOI
Publication Date
2017-12-04
Type
Conference Paper
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Citation
Tiddi, Ilaria, Bastianelli, Emanuele, Bardaro, Gianluca, d'Aquin, Mathieu, & Motta, Enrico. (2017). An ontology-based approach to improve the accessibility of ROS-based robotic systems. Paper presented at the Proceedings of the Knowledge Capture Conference, Austin, TX, USA, December 4–6.
Abstract
The focus of this work is to exploit ontologies to make robotic systems more accessible to non-expert users, therefore supporting the deployment of robot-integrated applications. Due to the increasing number of robotic platforms available for commercial use, robotic systems are nowadays being approached by users with di!erent backgrounds, who are often more interested in the robots’ high-level capabilities than their technical architecture. Without the right expertise however, using robots is restricted to the capabilities exposed by the platform provider, i.e. they can only be used as end products rather than as development platforms. Our hypothesis is that an ontological representation of the capabilities of robots could make these capabilities more accessible, reducing the complexity of robot programming and enabling non-experts to exploit these systems to a much larger extent. To demonstrate this, an ontology abstracting the capabilities exposed by the most common robotic middleware (ROS) is integrated in a system to allow non-experts to program robots of di!erent types and capabilities without previous knowledge either of the speci"c robotic platform being considered, or of the intricate systems used in its implementation. Our experiments, in which non-experts users had to con"gure the system in order to make robots achieve di!erent tasks, show how the e!orts required for realizing basic tasks using available robotic platforms can be sensibly reduced through our approach
Funder
Publisher
ACM
Publisher DOI
10.1145/3148011.3148014
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland