Path Tracking Hybrid A For Autonomous Agricultural Vehicles

We propose a path-tracking Hybrid A* planner and a coupled hierarchical Model Predictive Control (MPC) controller in scenarios involving the path smoothing of agricultural vehicles. For agricultural vehicles following reference paths on farmlands, especially during cross-furrow operations, a minimum...

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Bibliographic Details
Published in:arXiv.org 2024-11
Main Authors: Lu, Mingke, Gao, Han, Dai, Haijie, Lei, Qianli, Liu, Chang
Format: Article
Language:English
Subjects:
Agricultural vehicles
Algorithms
Collision avoidance
Constraints
Deviation
Path tracking
Predictive control
Real time
Smoothing
Online Access:Get full text
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Summary:We propose a path-tracking Hybrid A* planner and a coupled hierarchical Model Predictive Control (MPC) controller in scenarios involving the path smoothing of agricultural vehicles. For agricultural vehicles following reference paths on farmlands, especially during cross-furrow operations, a minimum deviation from the reference path is desired, in addition to the curvature constraints and body scale collision avoidance. Our contribution is threefold. (1) We propose the path-tracking Hybrid A*, which satisfies nonholonomic constraints and vehicle size collision avoidance, and devise new cost and heuristic functions to minimize the deviation degree. The path-tracking Hybrid A* can not only function in offline smoothing but also the real-time adjustment when confronted with unexpected obstacles. (2) We propose the hierarchical MPC to safely track the smoothed trajectory, using the initial solution solved by linearized MPC and nonlinear local adjustments around the initial solution. (3) We carry out extensive simulations with baseline comparisons based on real-world farm datasets to evaluate the performance of our algorithm.
ISSN:2331-8422