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A New Terrain Classification Framework Using Proprioceptive Sensors for Mobile Robots
Joint Authors
Dong, Mingming
Zhao, Kai
Gu, Liang
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-06
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Mobile robots that operate in real-world environments interact with the surroundings to generate complex acoustics and vibration signals, which carry rich information about the terrain.
This paper presents a new terrain classification framework that utilizes both acoustics and vibration signals resulting from the robot-terrain interaction.
As an alternative to handcrafted domain-specific feature extraction, a two-stage feature selection method combining ReliefF and mRMR algorithms was developed to select optimal feature subsets that carry more discriminative information.
As different data sources can provide complementary information, a multiclassifier combination method was proposed by considering a priori knowledge and fusing predictions from five data sources: one acoustic data source and four vibration data sources.
In this study, four conceptually different classifiers were employed to perform the classification, each with a different number of optimal features.
Signals were collected using a tracked robot moving at three different speeds on six different terrains.
The new framework successfully improved classification performance of different classifiers using the newly developed optimal feature subsets.
The greater improvement was observed for robot traversing at lower speeds.
American Psychological Association (APA)
Zhao, Kai& Dong, Mingming& Gu, Liang. 2017. A New Terrain Classification Framework Using Proprioceptive Sensors for Mobile Robots. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1190298
Modern Language Association (MLA)
Zhao, Kai…[et al.]. A New Terrain Classification Framework Using Proprioceptive Sensors for Mobile Robots. Mathematical Problems in Engineering No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1190298
American Medical Association (AMA)
Zhao, Kai& Dong, Mingming& Gu, Liang. A New Terrain Classification Framework Using Proprioceptive Sensors for Mobile Robots. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1190298
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190298