A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder
Position measurement is an essential process of mobile robot navigation. In this research, a Kalman Filter is applied to locating a mobile robot furnisher with an encoder and accelerometer. The accelerometer updates its position off-hand. It has an acceptable short period of stability. However, this...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Unviversity of Technology- Iraq
2022-01-01
|
| Series: | Engineering and Technology Journal |
| Subjects: | |
| Online Access: | https://etj.uotechnology.edu.iq/article_172913_67beafe68e596ef072005c840371e79f.pdf |
| _version_ | 1797337661558489088 |
|---|---|
| author | Ali Madhloom Firas Raheem Azad Kareem |
| author_facet | Ali Madhloom Firas Raheem Azad Kareem |
| author_sort | Ali Madhloom |
| collection | DOAJ |
| description | Position measurement is an essential process of mobile robot navigation. In this research, a Kalman Filter is applied to locating a mobile robot furnisher with an encoder and accelerometer. The accelerometer updates its position off-hand. It has an acceptable short period of stability. However, this stability will be decreased over time. The odometry model is utilized to measure the mobile robot's position and heading angle using encoders equipped with the wheels of the mobile robot. Moreover, the odometry model's errors exist because of the wheel rotating speed's integrative nature and non-systematic errors. In this work, the mobile robot position estimation in closed environments was studied. In order to obtain the optimal estimation, a Kalman filter was used to estimate mobile robots' position and velocity, where the Kalman filter has been designed for better assessment of the mobile robot position. The suggested configuration collects accelerometer and odometry reading to assure more delicate position knowledge than standalone odometry or accelerometer. The proposed method's position error has an acceptable level that is less than (0.2 m) for both easy and difficult paths. |
| first_indexed | 2024-03-08T09:16:50Z |
| format | Article |
| id | doaj.art-1b7c510cb622462fa79254184103a585 |
| institution | Directory Open Access Journal |
| issn | 1681-6900 2412-0758 |
| language | English |
| last_indexed | 2024-03-08T09:16:50Z |
| publishDate | 2022-01-01 |
| publisher | Unviversity of Technology- Iraq |
| record_format | Article |
| series | Engineering and Technology Journal |
| spelling | doaj.art-1b7c510cb622462fa79254184103a5852024-01-31T14:27:40ZengUnviversity of Technology- IraqEngineering and Technology Journal1681-69002412-07582022-01-0140126727410.30684/etj.v40i1.2082172913A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels EncoderAli Madhloom0Firas Raheem1Azad Kareem2Control and Systems Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.Control and Systems Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.Control and Systems Engineering Dept., University of Technology-Iraq, Alsina’a street, 10066 Baghdad, Iraq.Position measurement is an essential process of mobile robot navigation. In this research, a Kalman Filter is applied to locating a mobile robot furnisher with an encoder and accelerometer. The accelerometer updates its position off-hand. It has an acceptable short period of stability. However, this stability will be decreased over time. The odometry model is utilized to measure the mobile robot's position and heading angle using encoders equipped with the wheels of the mobile robot. Moreover, the odometry model's errors exist because of the wheel rotating speed's integrative nature and non-systematic errors. In this work, the mobile robot position estimation in closed environments was studied. In order to obtain the optimal estimation, a Kalman filter was used to estimate mobile robots' position and velocity, where the Kalman filter has been designed for better assessment of the mobile robot position. The suggested configuration collects accelerometer and odometry reading to assure more delicate position knowledge than standalone odometry or accelerometer. The proposed method's position error has an acceptable level that is less than (0.2 m) for both easy and difficult paths.https://etj.uotechnology.edu.iq/article_172913_67beafe68e596ef072005c840371e79f.pdfkalman filterodometryaccelerometerposition estimation |
| spellingShingle | Ali Madhloom Firas Raheem Azad Kareem A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder Engineering and Technology Journal kalman filter odometry accelerometer position estimation |
| title | A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder |
| title_full | A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder |
| title_fullStr | A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder |
| title_full_unstemmed | A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder |
| title_short | A Modified Kalman Filter-Based Mobile Robot Position Measurement using an Accelerometer and Wheels Encoder |
| title_sort | modified kalman filter based mobile robot position measurement using an accelerometer and wheels encoder |
| topic | kalman filter odometry accelerometer position estimation |
| url | https://etj.uotechnology.edu.iq/article_172913_67beafe68e596ef072005c840371e79f.pdf |
| work_keys_str_mv | AT alimadhloom amodifiedkalmanfilterbasedmobilerobotpositionmeasurementusinganaccelerometerandwheelsencoder AT firasraheem amodifiedkalmanfilterbasedmobilerobotpositionmeasurementusinganaccelerometerandwheelsencoder AT azadkareem amodifiedkalmanfilterbasedmobilerobotpositionmeasurementusinganaccelerometerandwheelsencoder AT alimadhloom modifiedkalmanfilterbasedmobilerobotpositionmeasurementusinganaccelerometerandwheelsencoder AT firasraheem modifiedkalmanfilterbasedmobilerobotpositionmeasurementusinganaccelerometerandwheelsencoder AT azadkareem modifiedkalmanfilterbasedmobilerobotpositionmeasurementusinganaccelerometerandwheelsencoder |