Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors
Robot mapping and exploration tasks are crucial for many robotic applications and allow mobile robots to autonomously navigate in unknown environments. An accurate model of the environment is, therefore, essential for the robots to localize and perform navigation. In this paper, we present a line se...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-05-01
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| Series: | SICE Journal of Control, Measurement, and System Integration |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.9746/jcmsi.13.138 |
| _version_ | 1797661042856165376 |
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| author | Ankit A. Ravankar Abhijeet Ravankar Takanori Emaru Yukinori Kobayashi |
| author_facet | Ankit A. Ravankar Abhijeet Ravankar Takanori Emaru Yukinori Kobayashi |
| author_sort | Ankit A. Ravankar |
| collection | DOAJ |
| description | Robot mapping and exploration tasks are crucial for many robotic applications and allow mobile robots to autonomously navigate in unknown environments. An accurate model of the environment is, therefore, essential for the robots to localize and perform navigation. In this paper, we present a line segment based mapping of indoor environments using range sensors for solving the simultaneous localization and mapping problem. The proposed method uses a modified Hough transform algorithm for line segment detection from laser range sensor data. The line extraction algorithm incorporates a noise model from the range sensor along with robot pose uncertainties. The proposed method is integrated with the extended Kalman filter. The extracted lines are merged to represent different structure in the environment correctly, and we show the results of our mapping method on simulated and real data sets. The experimental results demonstrate that the proposed method is capable of building an accurate line segment map of the environment for robot navigation. |
| first_indexed | 2024-03-11T18:38:33Z |
| format | Article |
| id | doaj.art-32a915d84c6f44d08ceeb02a630eb275 |
| institution | Directory Open Access Journal |
| issn | 1884-9970 |
| language | English |
| last_indexed | 2024-03-11T18:38:33Z |
| publishDate | 2020-05-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | SICE Journal of Control, Measurement, and System Integration |
| spelling | doaj.art-32a915d84c6f44d08ceeb02a630eb2752023-10-12T13:43:55ZengTaylor & Francis GroupSICE Journal of Control, Measurement, and System Integration1884-99702020-05-0113313814710.9746/jcmsi.13.13812103296Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range SensorsAnkit A. Ravankar0Abhijeet Ravankar1Takanori Emaru2Yukinori Kobayashi3Division of Human Mechanical Systems and Design, Faculty of Engineering, Hokkaido UniversityDepartment of Mechanical Engineering, Faculty of Engineering, Kitami Institute of TechnologyDivision of Human Mechanical Systems and Design, Faculty of Engineering, Hokkaido UniversityDivision of Human Mechanical Systems and Design, Faculty of Engineering, Hokkaido UniversityRobot mapping and exploration tasks are crucial for many robotic applications and allow mobile robots to autonomously navigate in unknown environments. An accurate model of the environment is, therefore, essential for the robots to localize and perform navigation. In this paper, we present a line segment based mapping of indoor environments using range sensors for solving the simultaneous localization and mapping problem. The proposed method uses a modified Hough transform algorithm for line segment detection from laser range sensor data. The line extraction algorithm incorporates a noise model from the range sensor along with robot pose uncertainties. The proposed method is integrated with the extended Kalman filter. The extracted lines are merged to represent different structure in the environment correctly, and we show the results of our mapping method on simulated and real data sets. The experimental results demonstrate that the proposed method is capable of building an accurate line segment map of the environment for robot navigation.http://dx.doi.org/10.9746/jcmsi.13.138robot mappingline segment extractionnoise modelingsimultaneous localization and mappingextended kalman filter |
| spellingShingle | Ankit A. Ravankar Abhijeet Ravankar Takanori Emaru Yukinori Kobayashi Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors SICE Journal of Control, Measurement, and System Integration robot mapping line segment extraction noise modeling simultaneous localization and mapping extended kalman filter |
| title | Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors |
| title_full | Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors |
| title_fullStr | Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors |
| title_full_unstemmed | Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors |
| title_short | Line Segment Extraction and Polyline Mapping for Mobile Robots in Indoor Structured Environments Using Range Sensors |
| title_sort | line segment extraction and polyline mapping for mobile robots in indoor structured environments using range sensors |
| topic | robot mapping line segment extraction noise modeling simultaneous localization and mapping extended kalman filter |
| url | http://dx.doi.org/10.9746/jcmsi.13.138 |
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