Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157498
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dc.contributor.authorFoo, Ryanen_US
dc.date.accessioned2022-05-18T13:16:28Z-
dc.date.available2022-05-18T13:16:28Z-
dc.date.issued2022-
dc.identifier.citationFoo, R. (2022). Learning based-gripper design, grasping and robot manipulation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157498en_US
dc.identifier.urihttps://hdl.handle.net/10356/157498-
dc.description.abstractThis 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.en_US
dc.language.isoenen_US
dc.publisherNanyang Technological Universityen_US
dc.relationB3094-211en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleLearning based-gripper design, grasping and robot manipulationen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorJiang Xudongen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
dc.contributor.organizationAgency for Science, Technology and Research (A*STAR)en_US
dc.contributor.supervisoremailEXDJiang@ntu.edu.sgen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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