Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors
Terrain classification provides valuable information for both control and navigation algorithms of wheeled mobile robots. In this paper, a novel online outdoor terrain classification algorithm is proposed for wheeled mobile robots. The algorithm is based on only time-domain features with both low co...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/15/3238 |
| _version_ | 1797586851495673856 |
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| author | Peter Sarcevic Dominik Csík Richard Pesti Sara Stančin Sašo Tomažič Vladimir Tadic Juvenal Rodriguez-Resendiz József Sárosi Akos Odry |
| author_facet | Peter Sarcevic Dominik Csík Richard Pesti Sara Stančin Sašo Tomažič Vladimir Tadic Juvenal Rodriguez-Resendiz József Sárosi Akos Odry |
| author_sort | Peter Sarcevic |
| collection | DOAJ |
| description | Terrain classification provides valuable information for both control and navigation algorithms of wheeled mobile robots. In this paper, a novel online outdoor terrain classification algorithm is proposed for wheeled mobile robots. The algorithm is based on only time-domain features with both low computational and low memory requirements, which are extracted from the inertial and magnetic sensor signals. Multilayer perceptron (MLP) neural networks are applied as classifiers. The algorithm is tested on a measurement database collected using a prototype measurement system for various outdoor terrain types. Different datasets were constructed based on various setups of processing window sizes, used sensor types, and robot speeds. To examine the possibilities of the three applied sensor types in the application, the features extracted from the measurement data of the different sensors were tested alone, in pairs and fused together. The algorithm is suitable to operate online on the embedded system of the mobile robot. The achieved results show that using the applied time-domain feature set the highest classification efficiencies on unknown data can be above 98%. It is also shown that the gyroscope provides higher classification rates than the widely used accelerometer. The magnetic sensor alone cannot be effectively used but fusing the data of this sensor with the data of the inertial sensors can improve the performance. |
| first_indexed | 2024-03-11T00:29:00Z |
| format | Article |
| id | doaj.art-053616fd25d442f9963cd7592d208382 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T00:29:00Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-053616fd25d442f9963cd7592d2083822023-11-18T22:48:21ZengMDPI AGElectronics2079-92922023-07-011215323810.3390/electronics12153238Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic SensorsPeter Sarcevic0Dominik Csík1Richard Pesti2Sara Stančin3Sašo Tomažič4Vladimir Tadic5Juvenal Rodriguez-Resendiz6József Sárosi7Akos Odry8Department of Mechatronics and Automation, Faculty of Engineering, University of Szeged, 6725 Szeged, HungaryDepartment of Mechatronics and Automation, Faculty of Engineering, University of Szeged, 6725 Szeged, HungaryDepartment of Mechatronics and Automation, Faculty of Engineering, University of Szeged, 6725 Szeged, HungaryFaculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, SloveniaInstitute of Informatics, University of Dunaújváros, 2400 Dunaújváros, HungaryFacultad de Ingeniería, Universidad Autónoma de Queretaro, Santiago de Querétaro 76010, MexicoDepartment of Mechatronics and Automation, Faculty of Engineering, University of Szeged, 6725 Szeged, HungaryDepartment of Mechatronics and Automation, Faculty of Engineering, University of Szeged, 6725 Szeged, HungaryTerrain classification provides valuable information for both control and navigation algorithms of wheeled mobile robots. In this paper, a novel online outdoor terrain classification algorithm is proposed for wheeled mobile robots. The algorithm is based on only time-domain features with both low computational and low memory requirements, which are extracted from the inertial and magnetic sensor signals. Multilayer perceptron (MLP) neural networks are applied as classifiers. The algorithm is tested on a measurement database collected using a prototype measurement system for various outdoor terrain types. Different datasets were constructed based on various setups of processing window sizes, used sensor types, and robot speeds. To examine the possibilities of the three applied sensor types in the application, the features extracted from the measurement data of the different sensors were tested alone, in pairs and fused together. The algorithm is suitable to operate online on the embedded system of the mobile robot. The achieved results show that using the applied time-domain feature set the highest classification efficiencies on unknown data can be above 98%. It is also shown that the gyroscope provides higher classification rates than the widely used accelerometer. The magnetic sensor alone cannot be effectively used but fusing the data of this sensor with the data of the inertial sensors can improve the performance.https://www.mdpi.com/2079-9292/12/15/3238terrain classificationwheeled mobile robotsaccelerometergyroscopemagnetometertime-domain analysis |
| spellingShingle | Peter Sarcevic Dominik Csík Richard Pesti Sara Stančin Sašo Tomažič Vladimir Tadic Juvenal Rodriguez-Resendiz József Sárosi Akos Odry Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors Electronics terrain classification wheeled mobile robots accelerometer gyroscope magnetometer time-domain analysis |
| title | Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors |
| title_full | Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors |
| title_fullStr | Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors |
| title_full_unstemmed | Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors |
| title_short | Online Outdoor Terrain Classification Algorithm for Wheeled Mobile Robots Equipped with Inertial and Magnetic Sensors |
| title_sort | online outdoor terrain classification algorithm for wheeled mobile robots equipped with inertial and magnetic sensors |
| topic | terrain classification wheeled mobile robots accelerometer gyroscope magnetometer time-domain analysis |
| url | https://www.mdpi.com/2079-9292/12/15/3238 |
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