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 (supervisor 1)
P.V. Kulkarni Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2020 Taeke de Haan
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Published Date

26-10-2020

Language

English

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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.

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