A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024.
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| Lenguaje: | English |
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Brac University
2024
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| Acceso en línea: | http://hdl.handle.net/10361/23077 |
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10361-230772024-06-03T21:00:56Z A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant Nafis, Allama Bakhtiyar Ahammed, Kawsar Oishi, Humaira Rahman Afroj, Sumya Raka, Rezwana Chaudhury Rahman, Md. Khalilur Department of Computer Science and Engineering, Brac University Robot Operating System (ROS) Simultaneous Localization and Map ping (SLAM) LiDAR Python Navigation Object detection SpeechRecognition Automation Artificial intelligence Robotics This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 50-54). "The rapid development of technology has led to the implementation of numerous solutions aimed at streamlining processes, one of which is the incorporation of artifi cial intelligence. The Simultaneous Localization and Mapping (SLAM) algorithm is fundamental to the restaurant robots operation and thereby determines its success or failure in carrying out its tasks. Few studies have looked at how well SLAM algo rithm work when combined with path planning for indoor location, even though the present two-dimensional Lidar-based SLAM algorithm has done quite well, especially in indoor scenarios. Planning and mapping routes for restaurant robots operating in an indoor setting is the topic of the following essay. The goal of this research is to find out how indoor location systems may make use of path planning algorithms in conjunction with SLAM methods. To verify the mapping data, real-time path planning must be investigated. For global path planning, the A* algorithm is used to find the most efficient route while avoiding obstacles. Local path planning makes use of the Dynamic window approach (DWA) algorithm. After extensive testing in simulated, emulated, and competitive indoor situations, it was determined that both the SLAM and path planning algorithms performed admirably. Further, we employ a speech recognition component to facilitate communication with clients and an ob ject identification model to track down lost items. Finally, experts may find this papers results useful when deciding which algorithms to use when building SLAM systems that meet their specific needs." Allama Bakhtiyar Nafis Kawsar Ahammed Humaira Rahman Oishi Rezwana Chaudhury Raka B.Sc in Computer Science 2024-06-03T05:03:49Z 2024-06-03T05:03:49Z 2024 2024-01 Thesis ID 18201085 ID 19101126 ID 19101391 ID 19301164 ID 19101128 http://hdl.handle.net/10361/23077 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 54 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Robot Operating System (ROS) Simultaneous Localization and Map ping (SLAM) LiDAR Python Navigation Object detection SpeechRecognition Automation Artificial intelligence Robotics |
| spellingShingle |
Robot Operating System (ROS) Simultaneous Localization and Map ping (SLAM) LiDAR Python Navigation Object detection SpeechRecognition Automation Artificial intelligence Robotics Nafis, Allama Bakhtiyar Ahammed, Kawsar Oishi, Humaira Rahman Afroj, Sumya Raka, Rezwana Chaudhury A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2024. |
| author2 |
Rahman, Md. Khalilur |
| author_facet |
Rahman, Md. Khalilur Nafis, Allama Bakhtiyar Ahammed, Kawsar Oishi, Humaira Rahman Afroj, Sumya Raka, Rezwana Chaudhury |
| format |
Thesis |
| author |
Nafis, Allama Bakhtiyar Ahammed, Kawsar Oishi, Humaira Rahman Afroj, Sumya Raka, Rezwana Chaudhury |
| author_sort |
Nafis, Allama Bakhtiyar |
| title |
A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| title_short |
A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| title_full |
A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| title_fullStr |
A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| title_full_unstemmed |
A comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| title_sort |
comprehensive study and analysis of artificial intelligence-based waiter robot in restaurant |
| publisher |
Brac University |
| publishDate |
2024 |
| url |
http://hdl.handle.net/10361/23077 |
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