ブドウ園におけるGPS不要のマルチタスク自律ナビゲーションのための非線形モデル予測制御
Non-linear Model Predictive Control for Multi-task GPS-free Autonomous Navigation in Vineyards
単一のRGB-Dカメラと非線形モデル予測制御を用いて、GPSが使えない密集したブドウ園でも列間を自律走行し、様々な作物間隔やタスクに対応する低コストなナビゲーションシステムを開発した。
著者: Matteo Sperti, Marco Ambrosio, Mauro Martini, Alessandro Navone, Andrea Ostuni, Marcello Chiaberge
分類: cs.RO
原文アブストラクト
Autonomous navigation is the foundation of agricultural robots. This paper focuses on developing an advanced autonomous navigation system for a rover operating within row-based crops. A position-agnostic system is proposed to address the challenging situation when standard localization methods, like GPS, fail due to unfavorable weather or obstructed signals. This breakthrough is especially vital in densely vegetated regions, including areas covered by thick tree canopies or pergola vineyards. This work proposed a novel system that leverages a single RGB-D camera and a Non-linear Model Predictive Control strategy to navigate through entire rows, adapting to various crop spacing. The presented solution demonstrates versatility in handling diverse crop densities, environmental factors, and multiple navigation tasks to support agricultural activities at an extremely cost-effective implementation. Experimental validation in simulated and real vineyards underscores the system's robustness and competitiveness in both standard row traversal and target objects approach.
