Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications
In recent years, the use of imaging sensors that produce a three-dimensional representation of the environment has become an efficient solution to increase the degree of perception of autonomous mobile robots. Accurate and dense 3D point clouds can be generated from traditional stereo systems and la...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2013-07-01
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| Series: | International Journal of Advanced Robotic Systems |
| Online Access: | https://doi.org/10.5772/56240 |
| _version_ | 1818879213815463936 |
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| author | Mauro Bellone Giulio Reina Nicola I. Giannoccaro Luigi Spedicato |
| author_facet | Mauro Bellone Giulio Reina Nicola I. Giannoccaro Luigi Spedicato |
| author_sort | Mauro Bellone |
| collection | DOAJ |
| description | In recent years, the use of imaging sensors that produce a three-dimensional representation of the environment has become an efficient solution to increase the degree of perception of autonomous mobile robots. Accurate and dense 3D point clouds can be generated from traditional stereo systems and laser scanners or from the new generation of RGB-D cameras, representing a versatile, reliable and cost-effective solution that is rapidly gaining interest within the robotics community. For autonomous mobile robots, it is critical to assess the traversability of the surrounding environment, especially when driving across natural terrain. In this paper, a novel approach to detect traversable and non-traversable regions of the environment from a depth image is presented that could enhance mobility and safety through integration with localization, control and planning methods. The proposed algorithm is based on the analysis of the normal vector of a surface obtained through Principal Component Analysis and it leads to the definition of a novel, so defined, Unevenness Point Descriptor. Experimental results, obtained with vehicles operating in indoor and outdoor environments, are presented to validate this approach. |
| first_indexed | 2024-12-19T14:26:30Z |
| format | Article |
| id | doaj.art-99bf94bf4bea4bcdabd6538dc8d346c2 |
| institution | Directory Open Access Journal |
| issn | 1729-8814 |
| language | English |
| last_indexed | 2024-12-19T14:26:30Z |
| publishDate | 2013-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | International Journal of Advanced Robotic Systems |
| spelling | doaj.art-99bf94bf4bea4bcdabd6538dc8d346c22022-12-21T20:17:36ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142013-07-011010.5772/5624010.5772_56240Unevenness Point Descriptor for Terrain Analysis in Mobile Robot ApplicationsMauro Bellone0Giulio Reina1Nicola I. Giannoccaro2Luigi Spedicato3 Department of Engineering for Innovation, University of Salento, Lecce, Italy Department of Engineering for Innovation, University of Salento, Lecce, Italy Department of Engineering for Innovation, University of Salento, Lecce, Italy Department of Engineering for Innovation, University of Salento, Lecce, ItalyIn recent years, the use of imaging sensors that produce a three-dimensional representation of the environment has become an efficient solution to increase the degree of perception of autonomous mobile robots. Accurate and dense 3D point clouds can be generated from traditional stereo systems and laser scanners or from the new generation of RGB-D cameras, representing a versatile, reliable and cost-effective solution that is rapidly gaining interest within the robotics community. For autonomous mobile robots, it is critical to assess the traversability of the surrounding environment, especially when driving across natural terrain. In this paper, a novel approach to detect traversable and non-traversable regions of the environment from a depth image is presented that could enhance mobility and safety through integration with localization, control and planning methods. The proposed algorithm is based on the analysis of the normal vector of a surface obtained through Principal Component Analysis and it leads to the definition of a novel, so defined, Unevenness Point Descriptor. Experimental results, obtained with vehicles operating in indoor and outdoor environments, are presented to validate this approach.https://doi.org/10.5772/56240 |
| spellingShingle | Mauro Bellone Giulio Reina Nicola I. Giannoccaro Luigi Spedicato Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications International Journal of Advanced Robotic Systems |
| title | Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications |
| title_full | Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications |
| title_fullStr | Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications |
| title_full_unstemmed | Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications |
| title_short | Unevenness Point Descriptor for Terrain Analysis in Mobile Robot Applications |
| title_sort | unevenness point descriptor for terrain analysis in mobile robot applications |
| url | https://doi.org/10.5772/56240 |
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