Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157498
Title: Learning based-gripper design, grasping and robot manipulation
Authors: Foo, Ryan
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Foo, R. (2022). Learning based-gripper design, grasping and robot manipulation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157498
Project: B3094-211
Abstract: This paper is the interim report for the final year project entitled ‘Learning Based-Gripper Design, Grasping and Robot Manipulation’. The purpose of this report is to document the project’s progress and achievements up to date and the problems that may have been encountered along the way. This report is 38 pages in length excluding the cover page, table of content and references. This project investigates development of optimum gripper design, grasping control for soft objects using deep reinforcement learning or evolutionary algorithms and generative deep learning models. The aim of the project is to learn grasping and manipulation skills for soft objects like fruits or leafy vegetables for indoor farming applications.
URI: https://hdl.handle.net/10356/157498
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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