Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops
In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses t...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/83/1/9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849342190667431936 |
|---|---|
| author | Ricardo Huaman Clayder Gonzalez Sixto Prado |
| author_facet | Ricardo Huaman Clayder Gonzalez Sixto Prado |
| author_sort | Ricardo Huaman |
| collection | DOAJ |
| description | In recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO and LIO algorithms—LeGO-LOAM, DLO, DLIO, FAST-LIO2, and Point-LIO—in a blueberry farm setting. Using an Ouster OS1-32 LiDAR mounted on a four-wheeled mobile robot, the algorithms were evaluated using the translational error metric across four distinct sequences. DLIO showed the highest accuracy across all sequences, with a minimal error of 0.126 m over a 230 m path, while FAST-LIO2 achieved its lowest translational error of 0.606 m on a U-shaped path. LeGO-LOAM, however, struggled due to the environment’s lack of linear and planar features. The results underscore the effectiveness and potential limitations of these algorithms in agricultural environments, offering insights into future improvements and adaptations. |
| format | Article |
| id | doaj-art-080a6ae1a34d4d269fc623b2605558b5 |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-080a6ae1a34d4d269fc623b2605558b52025-08-20T03:43:27ZengMDPI AGEngineering Proceedings2673-45912025-01-01831910.3390/engproc2025083009Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry CropsRicardo Huaman0Clayder Gonzalez1Sixto Prado2Multidisciplinary Research Laboratory, Universidad Privada Antenor Orrego, Trujillo 13008, PeruMultidisciplinary Research Laboratory, Universidad Privada Antenor Orrego, Trujillo 13008, PeruMultidisciplinary Research Laboratory, Universidad Privada Antenor Orrego, Trujillo 13008, PeruIn recent years, LiDAR Odometry (LO) and LiDAR Inertial Odometry (LIO) algorithms for robot localization have considerably improved, with significant advancements demonstrated in various benchmarks. However, their performance in agricultural environments remains underexplored. This study addresses this gap by evaluating five state-of-the-art LO and LIO algorithms—LeGO-LOAM, DLO, DLIO, FAST-LIO2, and Point-LIO—in a blueberry farm setting. Using an Ouster OS1-32 LiDAR mounted on a four-wheeled mobile robot, the algorithms were evaluated using the translational error metric across four distinct sequences. DLIO showed the highest accuracy across all sequences, with a minimal error of 0.126 m over a 230 m path, while FAST-LIO2 achieved its lowest translational error of 0.606 m on a U-shaped path. LeGO-LOAM, however, struggled due to the environment’s lack of linear and planar features. The results underscore the effectiveness and potential limitations of these algorithms in agricultural environments, offering insights into future improvements and adaptations.https://www.mdpi.com/2673-4591/83/1/9agricultural environmentmobile robotLiDAR odometryLiDAR inertial odometry |
| spellingShingle | Ricardo Huaman Clayder Gonzalez Sixto Prado Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops Engineering Proceedings agricultural environment mobile robot LiDAR odometry LiDAR inertial odometry |
| title | Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops |
| title_full | Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops |
| title_fullStr | Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops |
| title_full_unstemmed | Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops |
| title_short | Comparative Analysis of LiDAR Inertial Odometry Algorithms in Blueberry Crops |
| title_sort | comparative analysis of lidar inertial odometry algorithms in blueberry crops |
| topic | agricultural environment mobile robot LiDAR odometry LiDAR inertial odometry |
| url | https://www.mdpi.com/2673-4591/83/1/9 |
| work_keys_str_mv | AT ricardohuaman comparativeanalysisoflidarinertialodometryalgorithmsinblueberrycrops AT claydergonzalez comparativeanalysisoflidarinertialodometryalgorithmsinblueberrycrops AT sixtoprado comparativeanalysisoflidarinertialodometryalgorithmsinblueberrycrops |