Title
Probabilistic Analysis Applied to Cleaning Robots
Abstract
Robots are increasingly being used in industry and starting their way in our homes as well, particularly cleaning robots. The common techniques to analyze cleaning robots are based on simulations or statistical experiments made from filming robots' movements. In this work, we propose an alternative way of performing such an analysis by using Probabilistic Model Checking with the language and tool PRISM. We propose a PRISM characterization for robot motion algorithms that can be used as the input for simulations as well as check exhaustively whether an algorithm satisfies specific Probabilistic Temporal formulas. The proposed PRISM model allows measuring energy consumption and time to complete missions; such metrics are helpful to compare different algorithms considering specific environments. Furthermore, to ease the use of our work, we hide the PRISM syntax by proposing an imperative style DSL used to specify the algorithms. We illustrate those ideas with motion planning algorithms for home cleaning robots.
Year
DOI
Venue
2017
10.1109/IRI.2017.61
2017 IEEE International Conference on Information Reuse and Integration (IRI)
Keywords
Field
DocType
prism,dsl,probabilistic model checking
Motion planning,Data mining,Algorithm design,Digital subscriber line,Computer science,Probabilistic analysis of algorithms,Artificial intelligence,Probabilistic logic,Robot,Energy consumption,Syntax,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-5386-1563-8
0
0.34
References 
Authors
6
3
Name
Order
Citations
PageRank
Rafael Pereira de Araujo100.34
Alexandre Mota27211.09
Sidney Nogueira3495.69