Next Article in Journal
An Ultra-Wide Band Polarization-Independent Random Coding Metasurface for RCS Reduction
Previous Article in Journal
The Frequency-Domain Fusion Virtual Multi-Loop Feedback Control System with Measured Disturbance Feedforward Method in Telescopes
Previous Article in Special Issue
Optimized Proportional-Integral-Derivative Controller for Upper Limb Rehabilitation Robot
Open AccessArticle

RTPO: A Domain Knowledge Base for Robot Task Planning

College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Author to whom correspondence should be addressed.
Electronics 2019, 8(10), 1105;
Received: 21 August 2019 / Revised: 18 September 2019 / Accepted: 26 September 2019 / Published: 1 October 2019
(This article belongs to the Special Issue Cognitive Robotics & Control)
Knowledge can enhance the intelligence of robots’ high-level decision-making. However, there is no specific domain knowledge base for robot task planning in this field. Aiming to represent the knowledge in robot task planning, the Robot Task Planning Ontology (RTPO) is first designed and implemented in this work, so that robots can understand and know how to carry out task planning to reach the goal state. In this paper, the RTPO is divided into three parts: task ontology, environment ontology, and robot ontology, followed by a detailed description of these three types of knowledge, respectively. The OWL (Web Ontology Language) is adopted to represent the knowledge in robot task planning. Then, the paper proposes a method to evaluate the scalability and responsiveness of RTPO. Finally, the corresponding task planning algorithm is designed based on RTPO, and then the paper conducts experiments on the basis of the real robot TurtleBot3 to verify the usability of RTPO. The experimental results demonstrate that RTPO has good performance in scalability and responsiveness, and the robot can achieve given high-level tasks based on RTPO. View Full-Text
Keywords: ontology; robot task planning; knowledge base; knowledge representation ontology; robot task planning; knowledge base; knowledge representation
Show Figures

Figure 1

MDPI and ACS Style

Sun, X.; Zhang, Y.; Chen, J. RTPO: A Domain Knowledge Base for Robot Task Planning. Electronics 2019, 8, 1105.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop