Efficient maneuvering of automated agricultural vehicles with ground and
Grant Fondecyt 1140575.
Project Description and Objectives
This will develop motion control and task planning algorithms that take into account terramechanical parameters, crop field state and environment restrictions to improve the automation of crop care and harvesting and increase of the overall efficiency of the agricutural processes from seed to packing.
This project is carried out in collaboration with prof. Fernando Auat-Cheein, head of the Group of Industrial Robotics and Automation (GRAI) of the Universidad Tecnica Federico Santa Maria. The main project's objectives are:
- To develop wheel slippage estimators relying on terramechanic and vehicle-terrain interaction models, visual odometry, humidity sensors, LiDAR and inertial sensor fusion based on recursive stochastic methods.
- To develop maneuvering strategies considering constraints of the environment and the interaction dynamics between the vehicle and terrain to minimize slippage occurrences and increase safety in GPS-denied areas.