A Vision-Guided Robotic System for Grasping Harvested Tomato Trusses in Cluttered Environments

Autor:	Bent, Luuk van den, Coleman, Tomás, Babuska, Robert
Rok vydání:	2023
Předmět:	Computer Science - Robotics Computer Science - Artificial Intelligence Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	Currently, truss tomato weighing and packaging require significant manual work. The main obstacle to automation lies in the difficulty of developing a reliable robotic grasping system for already harvested trusses. We propose a method to grasp trusses that are stacked in a crate with considerable clutter, which is how they are commonly stored and transported after harvest. The method consists of a deep learning-based vision system to first identify the individual trusses in the crate and then determine a suitable grasping location on the stem. To this end, we have introduced a grasp pose ranking algorithm with online learning capabilities. After selecting the most promising grasp pose, the robot executes a pinch grasp without needing touch sensors or geometric models. Lab experiments with a robotic manipulator equipped with an eye-in-hand RGB-D camera showed a 100% clearance rate when tasked to pick all trusses from a pile. 93% of the trusses were successfully grasped on the first try, while the remaining 7% required more attempts. Comment: 7 pages, 7 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2309.17170 Zobrazit plný text záznamu View this record from Arxiv