Autonomous Vineyard Tracking Using a Four-Wheel-Steering Mobile Robot and a 2D LiDAR
Abstract
:1. Introduction
2. Materials and Methods
2.1. Row Detection Strategy
2.1.1. Pre-Processing
2.1.2. Detection Model Definition
2.1.3. Correlation Score Definition
- is the correlation score for the offset k between LiDAR data and template;
- z represents the LiDAR measurements on the Z-axis;
- m represents the values of the model data;
- and are the mean values of, respectively, LiDAR Z-axis data and model data.
2.1.4. Vine Structure Reconstruction
- —the lateral deviation of the retrieved point to the newest set-point in the robot frame;
- —the yaw of the robot computed with the odometry;
- and —the X and Y coordinates of the retrieved point;
- and —the X and Y coordinates of the previous aggregated set-point.
2.1.5. Trajectory Computation and Input Control
- y—the lateral deviation with respect to the reference trajectory;
- a and b, respectively, the slope and intercept computed by the least squares method;
- and —the coordinates of the robot computed through the system odometry;
- —the angular deviation;
- —the yaw of the robot computed through the system odometry.
2.2. Motion Control
2.2.1. Mobile Robot Modeling
2.2.2. Control Strategy 1: Backstepping Position/Orientation Control
- Step 1: Computation of the target angular deviation
- Step 2: Control law for the front steering angle
- Step 3: Control law for the rear steering angle
2.2.3. Control Strategy 2: Lateral Errors Regulation
- Step 1: Modeling of the tracking errors
- Step 2: Control law for the rear steering angle
- Step 3: Control law for the front steering angle
3. Results
3.1. Simulation Testbed—Digitized Experimental Vineyard with Terrain Variability
3.2. Validation on Summer Vineyard
3.3. Validation on Winter Vineyard
3.4. Discussion
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Settings/Scenario | Vine Model Parameters | LiDAR Position | Control Parameters | ||||||
---|---|---|---|---|---|---|---|---|---|
Width (Index) | Height (m) | Corr. Threshold | x (m) | y (m) | z (m) | Strategy 1 | Strategy 2 | ||
Summer Vineyard | 10.0 | 1.0 | 0.25 | 1.0 | 0 | 2.0 | 45 | = −0.9 = 1.0 = 1.0 | = 0.35 = 0.35 |
Winter Vineyard | 5.0 | 1.0 | 0.25 | 1.0 | 0 | 2.0 | 45 | = −0.9 = 1.0 = 1.0 | = 0.35 = 0.35 |
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Iberraken, D.; Gaurier, F.; Roux, J.-C.; Chaballier, C.; Lenain, R. Autonomous Vineyard Tracking Using a Four-Wheel-Steering Mobile Robot and a 2D LiDAR. AgriEngineering 2022, 4, 826-846. https://doi.org/10.3390/agriengineering4040053
Iberraken D, Gaurier F, Roux J-C, Chaballier C, Lenain R. Autonomous Vineyard Tracking Using a Four-Wheel-Steering Mobile Robot and a 2D LiDAR. AgriEngineering. 2022; 4(4):826-846. https://doi.org/10.3390/agriengineering4040053
Chicago/Turabian StyleIberraken, Dimia, Florian Gaurier, Jean-Christophe Roux, Colin Chaballier, and Roland Lenain. 2022. "Autonomous Vineyard Tracking Using a Four-Wheel-Steering Mobile Robot and a 2D LiDAR" AgriEngineering 4, no. 4: 826-846. https://doi.org/10.3390/agriengineering4040053