四足歩行ロボットによるビニヤード自律ナビゲーションのためのコンピュータビジョンに基づくリアルタイムウェイポイント生成
Computer-Vision Based Real Time Waypoint Generation for Autonomous Vineyard Navigation with Quadruped Robots
四足歩行ロボットHyQRealにアームと視覚センサを搭載し、コンピュータビジョンでブドウの木を検出してウェイポイントを生成、自律的に接近するナビゲーション手法を提案した。平均誤差21.5cmで動作するが、検出精度の向上が課題。
著者: Lee Milburn, Juan Gamba, Miguel Fernandes, Claudio Semini
分類: cs.RO
原文アブストラクト
The VINUM project seeks to address the shortage of skilled labor in modern vineyards by introducing a cutting-edge mobile robotic solution. Leveraging the capabilities of the quadruped robot, HyQReal, this system, equipped with arm and vision sensors, offers autonomous navigation and winter pruning of grapevines reducing the need for human intervention. At the heart of this approach lies an architecture that empowers the robot to easily navigate vineyards, identify grapevines with unparalleled accuracy, and approach them for pruning with precision. A state machine drives the process, deftly switching between various stages to ensure seamless and efficient task completion. The system's performance was assessed through experimentation, focusing on waypoint precision and optimizing the robot's workspace for single-plant operations. Results indicate that the architecture is highly reliable, with a mean error of 21.5cm and a standard deviation of 17.6cm for HyQReal. However, improvements in grapevine detection accuracy are necessary for optimal performance. This work is based on a computer-vision-based navigation method for quadruped robots in vineyards, opening up new possibilities for selective task automation. The system's architecture works well in ideal weather conditions, generating and arriving at precise waypoints that maximize the attached robotic arm's workspace. This work is an extension of our short paper presented at the Italian Conference on Robotics and Intelligent Machines (I-RIM).
