Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras
1
School of Information Technology and Communication, Hanoi University of Science and Technology, Hanoi, Vietnam
2
School of Information Science and Engineering, Lanzhou University, Lanzhou 730030, China
*
Author to whom correspondence should be addressed.
Machines 2018, 6(4), 46; https://doi.org/10.3390/machines6040046
Received: 4 August 2018 / Revised: 12 September 2018 / Accepted: 28 September 2018 / Published: 3 October 2018
Human behaviour demonstrates environmental awareness and self-awareness which is used to arrive at decisions and actions or reach conclusions based on reasoning and inference. Environmental awareness and self-awareness are traits which autonomous robotic systems must have to effectively plan an optimal route and operate in dynamic operating environments. This paper proposes a novel approach to enable autonomous robotic systems to achieve efficient coverage path planning, which combines adaptation with knowledge reasoning techniques and hedge algebras to achieve optimal coverage path planning in multiple decision-making under dynamic operating environments. To evaluate the proposed approach we have implemented it in a mobile cleaning robot. The results demonstrate the ability to avoid static and dynamic (moving) obstacles while achieving efficient coverage path planning with low repetition rates. While alternative current coverage path planning algorithms have achieved acceptable results, our reported results have demonstrated a significant performance improvement over the alternative coverage path planning algorithms.
View Full-Text
Keywords:
autonomous robotic systems; coverage path planning; knowledge reasoning and inference; hedge algebras; decision-support systems; machine cognition; machine consciousness; self-awareness; environmental awareness
▼
Show Figures
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Van Pham, H.; Moore, P. Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras. Machines 2018, 6, 46. https://doi.org/10.3390/machines6040046
AMA Style
Van Pham H, Moore P. Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras. Machines. 2018; 6(4):46. https://doi.org/10.3390/machines6040046
Chicago/Turabian StyleVan Pham, Hai; Moore, Philip. 2018. "Robot Coverage Path Planning under Uncertainty Using Knowledge Inference and Hedge Algebras" Machines 6, no. 4: 46. https://doi.org/10.3390/machines6040046
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
Search more from Scilit