An assistive robotics control system based on speech semantic recognition
Since 90’s era, many researchers and organizations are working on assistive technologies to ease the disabilities people to move around freely, independence, comfort and have the capabilities to enjoy life to the fullest. Nowadays, most of assistive technologies such as manual wheelchairs are propel...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2019
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/669/1/24p%20SITI%20NUR%20ATEEQA%20MOHAMAD.pdf http://eprints.uthm.edu.my/669/2/SITI%20NUR%20ATEEQA%20MOHAMAD%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/669/3/SITI%20NUR%20ATEEQA%20MOHAMAD%20WATERMARK.pdf |
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| Summary: | Since 90’s era, many researchers and organizations are working on assistive technologies to ease the disabilities people to move around freely, independence, comfort and have the capabilities to enjoy life to the fullest. Nowadays, most of assistive technologies such as manual wheelchairs are propelled by patients sitting on the chair and physically turning the large rear wheels with hand or need helpers to push the chair by handles from behind of the wheelchair. Meanwhile, most of voice command wheelchair unable to deal with an unknown word and cannot take spontaneous speech data from the native speakers. Thus, this project proposes a method of control system for an assistive robotic based on speech semantic recognition through hardware implementation. Consequently, the purpose of this project is to develop a system based on speech semantic or meaning or the interpretation of a word, sentence, or others language form that can be used for an assistive robot. The mobile robot is represented as a wheelchair and a home prototype floor plan is represented as a house with four rooms (living room, toilet, kitchen and bedroom). The mobile robot moves according to the semantic of user commands and the commands are given on Android application Arduino Bluetooth Controller. This Android application is used to catch the command using Google Voice and send the command through Bluetooth HC-05 that connected to the Arduino. Moreover, the obstacle avoidance sensor used for this project is SHARP IR Distance Measurement sensor that standby when their obstacles in front of this mobile robot and the navigation system of this mobile robot are using Simultaneous Localization and Mapping (SLAM). The effectiveness of this mobile robot has been tested using qualitative method by gathered 12 respondents to test this mobile robot on the floor plan. The total effectiveness of this mobile robot is 83%. This mobile robot is still effective but there are some parts that are still missing and need to be improved. Finally, the main contribution of this project is to help physically handicapped people such as patients who cannot move their feet by controlling using speech meanings through helpful robotics applications. |
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