Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot
This paper proposes a method for mobile robot localization in a partially unknown indoor environment. The method fuses two types of range measurements: the range from the robot to the beacons measured by ultrasonic sensors and the range from the robot to the walls surrounding the robot measured by a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-05-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/15/5/11050 |
| _version_ | 1811300783897968640 |
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| author | Nak Yong Ko Tae-Yong Kuc |
| author_facet | Nak Yong Ko Tae-Yong Kuc |
| author_sort | Nak Yong Ko |
| collection | DOAJ |
| description | This paper proposes a method for mobile robot localization in a partially unknown indoor environment. The method fuses two types of range measurements: the range from the robot to the beacons measured by ultrasonic sensors and the range from the robot to the walls surrounding the robot measured by a laser range finder (LRF). For the fusion, the unscented Kalman filter (UKF) is utilized. Because finding the Jacobian matrix is not feasible for range measurement using an LRF, UKF has an advantage in this situation over the extended KF. The locations of the beacons and range data from the beacons are available, whereas the correspondence of the range data to the beacon is not given. Therefore, the proposed method also deals with the problem of data association to determine which beacon corresponds to the given range data. The proposed approach is evaluated using different sets of design parameter values and is compared with the method that uses only an LRF or ultrasonic beacons. Comparative analysis shows that even though ultrasonic beacons are sparsely populated, have a large error and have a slow update rate, they improve the localization performance when fused with the LRF measurement. In addition, proper adjustment of the UKF design parameters is crucial for full utilization of the UKF approach for sensor fusion. This study contributes to the derivation of a UKF-based design methodology to fuse two exteroceptive measurements that are complementary to each other in localization. |
| first_indexed | 2024-04-13T06:57:25Z |
| format | Article |
| id | doaj.art-f80c19582b434d21aafe8a901403edea |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:57:25Z |
| publishDate | 2015-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f80c19582b434d21aafe8a901403edea2022-12-22T02:57:13ZengMDPI AGSensors1424-82202015-05-01155110501107510.3390/s150511050s150511050Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile RobotNak Yong Ko0Tae-Yong Kuc1Department of Electronics Engineering, Chosun University, 375 Seosuk-dong Dong-gu, Gwangju 501-759, KoreaCollege of Information and Communication Engineering, Sungkyunkwan University, 300 Cheoncheon-dong Jangan-gu Suwon, Gyeonggi-do 440-746, KoreaThis paper proposes a method for mobile robot localization in a partially unknown indoor environment. The method fuses two types of range measurements: the range from the robot to the beacons measured by ultrasonic sensors and the range from the robot to the walls surrounding the robot measured by a laser range finder (LRF). For the fusion, the unscented Kalman filter (UKF) is utilized. Because finding the Jacobian matrix is not feasible for range measurement using an LRF, UKF has an advantage in this situation over the extended KF. The locations of the beacons and range data from the beacons are available, whereas the correspondence of the range data to the beacon is not given. Therefore, the proposed method also deals with the problem of data association to determine which beacon corresponds to the given range data. The proposed approach is evaluated using different sets of design parameter values and is compared with the method that uses only an LRF or ultrasonic beacons. Comparative analysis shows that even though ultrasonic beacons are sparsely populated, have a large error and have a slow update rate, they improve the localization performance when fused with the LRF measurement. In addition, proper adjustment of the UKF design parameters is crucial for full utilization of the UKF approach for sensor fusion. This study contributes to the derivation of a UKF-based design methodology to fuse two exteroceptive measurements that are complementary to each other in localization.http://www.mdpi.com/1424-8220/15/5/11050fusing measurementsmobile robotlaser range finderultrasonic beaconsdata associationunscented Kalman filter |
| spellingShingle | Nak Yong Ko Tae-Yong Kuc Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot Sensors fusing measurements mobile robot laser range finder ultrasonic beacons data association unscented Kalman filter |
| title | Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot |
| title_full | Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot |
| title_fullStr | Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot |
| title_full_unstemmed | Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot |
| title_short | Fusing Range Measurements from Ultrasonic Beacons and a Laser Range Finder for Localization of a Mobile Robot |
| title_sort | fusing range measurements from ultrasonic beacons and a laser range finder for localization of a mobile robot |
| topic | fusing measurements mobile robot laser range finder ultrasonic beacons data association unscented Kalman filter |
| url | http://www.mdpi.com/1424-8220/15/5/11050 |
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