Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm
To address issues such as the confusion of environmental feature points and significant pose information errors in chili fields, an autonomous navigation system based on multi-sensor data fusion and an optimized TEB (Timed Elastic Band) algorithm is proposed. The system’s positioning component integ...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/14/12/2872 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846106361497124864 |
|---|---|
| author | Weikang Han Qihang Gu Huaning Gu Rui Xia Yuan Gao Zhenbao Zhou Kangya Luo Xipeng Fang Yali Zhang |
| author_facet | Weikang Han Qihang Gu Huaning Gu Rui Xia Yuan Gao Zhenbao Zhou Kangya Luo Xipeng Fang Yali Zhang |
| author_sort | Weikang Han |
| collection | DOAJ |
| description | To address issues such as the confusion of environmental feature points and significant pose information errors in chili fields, an autonomous navigation system based on multi-sensor data fusion and an optimized TEB (Timed Elastic Band) algorithm is proposed. The system’s positioning component integrates pose data from the GNSS and the IMU inertial navigation system, and corrects positioning errors caused by the clutter of LiDAR environmental feature points. To solve the problem of local optimization and excessive collision handling in the TEB algorithm during the path planning phase, the weight parameters are optimized based on environmental characteristics, thereby reducing errors in optimal path determination. Furthermore, considering the topographic inclination between rows (5–15°), 10 sets of comparison tests were conducted. The results show that the navigation system reduced the average path length by 0.58 m, shortened the average time consumption by 2.55 s, and decreased the average target position offset by 4.3 cm. In conclusion, the multi-sensor data fusion and optimized TEB algorithm demonstrate significant potential for realizing autonomous navigation in the narrow and complex environment of chili fields. |
| format | Article |
| id | doaj-art-9adeffdd31bc41e88f445e08e4160559 |
| institution | Kabale University |
| issn | 2073-4395 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj-art-9adeffdd31bc41e88f445e08e41605592024-12-27T14:04:14ZengMDPI AGAgronomy2073-43952024-12-011412287210.3390/agronomy14122872Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB AlgorithmWeikang Han0Qihang Gu1Huaning Gu2Rui Xia3Yuan Gao4Zhenbao Zhou5Kangya Luo6Xipeng Fang7Yali Zhang8College of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaTo address issues such as the confusion of environmental feature points and significant pose information errors in chili fields, an autonomous navigation system based on multi-sensor data fusion and an optimized TEB (Timed Elastic Band) algorithm is proposed. The system’s positioning component integrates pose data from the GNSS and the IMU inertial navigation system, and corrects positioning errors caused by the clutter of LiDAR environmental feature points. To solve the problem of local optimization and excessive collision handling in the TEB algorithm during the path planning phase, the weight parameters are optimized based on environmental characteristics, thereby reducing errors in optimal path determination. Furthermore, considering the topographic inclination between rows (5–15°), 10 sets of comparison tests were conducted. The results show that the navigation system reduced the average path length by 0.58 m, shortened the average time consumption by 2.55 s, and decreased the average target position offset by 4.3 cm. In conclusion, the multi-sensor data fusion and optimized TEB algorithm demonstrate significant potential for realizing autonomous navigation in the narrow and complex environment of chili fields.https://www.mdpi.com/2073-4395/14/12/2872multi-sensordata fusionpositioningpath planningoptimized TEB algorithm |
| spellingShingle | Weikang Han Qihang Gu Huaning Gu Rui Xia Yuan Gao Zhenbao Zhou Kangya Luo Xipeng Fang Yali Zhang Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm Agronomy multi-sensor data fusion positioning path planning optimized TEB algorithm |
| title | Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm |
| title_full | Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm |
| title_fullStr | Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm |
| title_full_unstemmed | Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm |
| title_short | Design of Chili Field Navigation System Based on Multi-Sensor and Optimized TEB Algorithm |
| title_sort | design of chili field navigation system based on multi sensor and optimized teb algorithm |
| topic | multi-sensor data fusion positioning path planning optimized TEB algorithm |
| url | https://www.mdpi.com/2073-4395/14/12/2872 |
| work_keys_str_mv | AT weikanghan designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT qihanggu designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT huaninggu designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT ruixia designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT yuangao designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT zhenbaozhou designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT kangyaluo designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT xipengfang designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm AT yalizhang designofchilifieldnavigationsystembasedonmultisensorandoptimizedtebalgorithm |