Learning based-gripper design, grasping and robot manipulation

• Main Author: Foo, Ryan
• Other Authors: Jiang Xudong
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/157498
• Institution: Nanyang Technological University

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.