A Geometry-Based Grasping Method for Vine Tomato

Master thesis (2020)

Authors

T. de Haan Mechanical Engineering

Contributors

R. Babuska Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering (mentor)
P.V. Kulkarni Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering (graduation committee member)
Faculty
Mechanical Engineering, Mechanical Engineering
Copyright: © 2020 Taeke de Haan
More Info
expand_more

Published Date

26-10-2020

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Mechanical Engineering

Abstract

In this thesis, a geometry-based grasping method for vine-tomato is proposed. The method utilizes a geometric model of the robotic hand and truss to determine an optimal grasping location on the truss stem. This allows grasping a truss without requiring delicate contact sensors or complex mechanical models. A computer vision pipeline is developed to identify required geometric features of the tomatoes and truss stem. To validate the proposed grasping method, real-world experiments were conducted using an RGB-D camera and a robotic manipulator. By combining plastic and real stems with artificial tomatoes two types of trusses were constructed. A success rate of 92% was obtained on the former type and 83% on the latter. The newly developed method is shown to be capable of grasping vine tomato. For real-world implementation future studies are needed, several recommendations are given.

Files

Main.pdf
(pdf | 64.6 Mb)
- Embargo expired in 26-10-2021
Unknown license