Giving smart devices a body

The field of robotics is advancing rapidly. Newer and smarter technologies are being developed for industrial applications, making advanced robotics a pillar of Industry 4.0. However, adoption rate of such technology for domestic applications is still low. An aspect of technology that has had a huge...

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Bibliographic Details
Main Author: Ng, Jing Hang
Other Authors: Dino Accoto
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/141821
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author Ng, Jing Hang
author2 Dino Accoto
author_facet Dino Accoto
Ng, Jing Hang
author_sort Ng, Jing Hang
collection NTU
description The field of robotics is advancing rapidly. Newer and smarter technologies are being developed for industrial applications, making advanced robotics a pillar of Industry 4.0. However, adoption rate of such technology for domestic applications is still low. An aspect of technology that has had a huge penetration in the populace is smartphones, where people use for work, play, and stuff. The technology in smartphones have advanced by leaps and bounds over the years and are now able to execute computations that even exceeds laptops from a decade ago. Application developers have also been able to take advantage of the capabilities of these smartphones by developing applications empowered with machine intelligence such as face filters, facial recognition, speech-to-text, image classifier, text classifier and other developments with machine learning platforms such as TensorFlow. With the intention of making use of the smart capabilities of a smartphone and integrating it with a robotic platform to conceptualize a smartphone enabled robot to improve the population penetration of robots in domestic situations, this project was established. The goal is to create two Android applications. The first will use the object detection and tracking capabilities of the TensorFlow Lite API to instruct a robotic platform. The second uses the TensorFlow Lite API’s speech recognition capabilities to move on the robotic platform on a user’s command. The project involved Android programming, interfacing with the TensorFlow Lite API, creating appropriate instructions and interfacing with the robot through the Universal Serial Bus (USB). The application was not implemented successfully, due to time and resource constraint that led to a lack of Android application debugging, so stability is not measurable. The author was able to identify the main issues with the application and architecture of the setup. However, this report intends to document the progress of the project as well as the insights gained from the project so that a better version of the application can be developed.
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spelling ntu-10356/1418212023-03-04T19:31:16Z Giving smart devices a body Ng, Jing Hang Dino Accoto School of Mechanical and Aerospace Engineering daccoto@ntu.edu.sg Engineering::Mechanical engineering::Mechatronics Engineering::Mechanical engineering::Robots The field of robotics is advancing rapidly. Newer and smarter technologies are being developed for industrial applications, making advanced robotics a pillar of Industry 4.0. However, adoption rate of such technology for domestic applications is still low. An aspect of technology that has had a huge penetration in the populace is smartphones, where people use for work, play, and stuff. The technology in smartphones have advanced by leaps and bounds over the years and are now able to execute computations that even exceeds laptops from a decade ago. Application developers have also been able to take advantage of the capabilities of these smartphones by developing applications empowered with machine intelligence such as face filters, facial recognition, speech-to-text, image classifier, text classifier and other developments with machine learning platforms such as TensorFlow. With the intention of making use of the smart capabilities of a smartphone and integrating it with a robotic platform to conceptualize a smartphone enabled robot to improve the population penetration of robots in domestic situations, this project was established. The goal is to create two Android applications. The first will use the object detection and tracking capabilities of the TensorFlow Lite API to instruct a robotic platform. The second uses the TensorFlow Lite API’s speech recognition capabilities to move on the robotic platform on a user’s command. The project involved Android programming, interfacing with the TensorFlow Lite API, creating appropriate instructions and interfacing with the robot through the Universal Serial Bus (USB). The application was not implemented successfully, due to time and resource constraint that led to a lack of Android application debugging, so stability is not measurable. The author was able to identify the main issues with the application and architecture of the setup. However, this report intends to document the progress of the project as well as the insights gained from the project so that a better version of the application can be developed. Bachelor of Engineering (Mechanical Engineering) 2020-06-11T02:12:22Z 2020-06-11T02:12:22Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/141821 en application/pdf Nanyang Technological University
spellingShingle Engineering::Mechanical engineering::Mechatronics
Engineering::Mechanical engineering::Robots
Ng, Jing Hang
Giving smart devices a body
title Giving smart devices a body
title_full Giving smart devices a body
title_fullStr Giving smart devices a body
title_full_unstemmed Giving smart devices a body
title_short Giving smart devices a body
title_sort giving smart devices a body
topic Engineering::Mechanical engineering::Mechatronics
Engineering::Mechanical engineering::Robots
url https://hdl.handle.net/10356/141821
work_keys_str_mv AT ngjinghang givingsmartdevicesabody