Tactile identification of textures using machine learning/ deep learning
In the recent years, Artificial Intelligence technology has grown exponentially, especially in sub-areas such as Machine Learning and Deep Learning. However, many of its applications rely on image acquisition techniques to obtain datasets. This project seeks to establish a method to identify a...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/157614 |
| _version_ | 1811697620229292032 |
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| author | Goh, Jun Bin |
| author2 | Leong Wei Lin |
| author_facet | Leong Wei Lin Goh, Jun Bin |
| author_sort | Goh, Jun Bin |
| collection | NTU |
| description | In the recent years, Artificial Intelligence technology has grown exponentially, especially
in sub-areas such as Machine Learning and Deep Learning. However, many of its
applications rely on image acquisition techniques to obtain datasets. This project seeks to
establish a method to identify an object, based on its haptic properties, and using Machine
Learning and/or Deep Learning techniques.
In this project, different materials are tested across a consistent laboratory setup by
applying the same amount of force over time through the use of a robotic arm in a
laboratory setup. The pressure received on each material is recorded as a dataset. The
collected datasets are then fed into a coded program containing a Machine Learning/
Deep Learning algorithm, where the algorithm learns the characteristics of each labelled
dataset and establishes a trained model based on the set of material and algorithm.
Thereafter, the unseen dataset of a material can be tested on the newly trained Machine
Learning/ Deep Learning model, to predict and identify the material as a result.
This report will cover on the considerations behind the project, the documentation of
experimental processes and parameters, and provide an analysis and conclusion for the
above. |
| first_indexed | 2024-10-01T07:58:09Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/157614 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:58:09Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1576142023-07-07T19:35:00Z Tactile identification of textures using machine learning/ deep learning Goh, Jun Bin Leong Wei Lin School of Electrical and Electronic Engineering wlleong@ntu.edu.sg Engineering::Electrical and electronic engineering::Electric apparatus and materials In the recent years, Artificial Intelligence technology has grown exponentially, especially in sub-areas such as Machine Learning and Deep Learning. However, many of its applications rely on image acquisition techniques to obtain datasets. This project seeks to establish a method to identify an object, based on its haptic properties, and using Machine Learning and/or Deep Learning techniques. In this project, different materials are tested across a consistent laboratory setup by applying the same amount of force over time through the use of a robotic arm in a laboratory setup. The pressure received on each material is recorded as a dataset. The collected datasets are then fed into a coded program containing a Machine Learning/ Deep Learning algorithm, where the algorithm learns the characteristics of each labelled dataset and establishes a trained model based on the set of material and algorithm. Thereafter, the unseen dataset of a material can be tested on the newly trained Machine Learning/ Deep Learning model, to predict and identify the material as a result. This report will cover on the considerations behind the project, the documentation of experimental processes and parameters, and provide an analysis and conclusion for the above. Bachelor of Engineering (Information Engineering and Media) 2022-05-21T07:56:20Z 2022-05-21T07:56:20Z 2022 Final Year Project (FYP) Goh, J. B. (2022). Tactile identification of textures using machine learning/ deep learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157614 https://hdl.handle.net/10356/157614 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering::Electric apparatus and materials Goh, Jun Bin Tactile identification of textures using machine learning/ deep learning |
| title | Tactile identification of textures using machine learning/ deep learning |
| title_full | Tactile identification of textures using machine learning/ deep learning |
| title_fullStr | Tactile identification of textures using machine learning/ deep learning |
| title_full_unstemmed | Tactile identification of textures using machine learning/ deep learning |
| title_short | Tactile identification of textures using machine learning/ deep learning |
| title_sort | tactile identification of textures using machine learning deep learning |
| topic | Engineering::Electrical and electronic engineering::Electric apparatus and materials |
| url | https://hdl.handle.net/10356/157614 |
| work_keys_str_mv | AT gohjunbin tactileidentificationoftexturesusingmachinelearningdeeplearning |