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Robot Waiter System

About the Robot Waiter

In the fast-paced restaurant industry, ensuring quick and efficient service is crucial. Traditional waiter systems face challenges such as delays, human errors, and high labor costs. Our project, "The Robot Waiter," aims to solve these issues by introducing a remotely controlled robot that can deliver orders to customers efficiently. Unlike fully automated systems, this robot offers a balance of human oversight and robotic precision, making it adaptable to dynamic environments. The impact of this solution includes improved service efficiency, reduced labor dependency, and an enhanced customer experience. By leveraging online control systems, restaurants can operate the robot with minimal training and flexibility, even in complex layouts.

High- Level Diagram

System Design Image

System Flow Overview

Admin

Employee Interface

MQTT to AWS

Robot Interface

AWS Routing

Real-Time Control

Hover over a step to see more info

Circuit Diagram

Circuit Diagram

Raspberry Pi 3B

Acts as the brain of the robot, handling processing and network communication via MQTT/WebSockets.

12V Battery

Powers the entire robot, providing necessary voltage to motors, sensors, and the processing unit.

HC-SR04 Sensors

Used for obstacle detection and navigation, ensuring smooth delivery without collisions.

Motor Driver

Controls the movement of the robot by adjusting voltage and current to the gear motors.

Buck Converter

Steps down 12V to 5V for powering the Raspberry Pi safely and efficiently.

Camera Module

Captures real-time video for visual monitoring and helps with remote navigation.

Project Timeline

Project Proposal

Initial idea and proposal submission.

January 2025

System Design

High-level architecture finalized.

February 2025

Hardware Assembly

Robot structure built with sensors.

March 2025

Software Integration

Frontend and backend integrated.

April 2025

Testing & Evaluation

System tested and finalized.

May 2025

Budget

Category Item Description Qty Unit Cost (LKR) Total Cost (LKR)
User Interaction Camera Module Raspberry Pi Camera Module 1 1 1800 1800
Display HDMI Display 1 6000 6000
Power System Battery 12V UPS Battery 1 5000 5000
Charger 12V Charger 1 2500 2500
Buck Converter 12V to 5V Converter 1 150 150
Navigation Motors JGB 520 100 RPM Gear Motors 4 1390 5560
Wheels Rubber Wheels 4 190 760
Ultrasonic Sensors HC-SR04 2 500 1000
Structure Tray Frame Aluminium Frame 1 2000 2000
Chassis Wooden Chassis + Assembly Cost 1 1000 1000
Lathe Works Axle Lathe Processing 4 600 2400
Processing Unit Raspberry Pi 3 B 1.4GHz 64-bit Quad-Core Processor 1 20000 20000
Total: 49,970 LKR

Testing

Hardware Testing

System Design Image
We conducted individual tests for each sensor to ensure proper functionality: Camera Module: Verified video streaming capability using IoT Core, ensuring real-time image capture and transmission to the frontend. Ultrasonic Sensors: Tested distance measurement accuracy, sending real-time obstacle data via AWS IoT Core. Gyroscope Sensor: Evaluated motion tracking and orientation updates, integrating it with IoT Core for real-time monitoring in the frontend.

Software Testing

System Design Image

MQTT on AWS IoT Core: Verified stable communication between the robot and the frontend by configuring MQTT publishers (robot commands) and subscribers (robot status updates). AWS Cognito Authentication: Tested the ability to gain temporary access tokens for the React frontend, reducing the need for constant requests through our Node.js server. This enhances efficiency while ensuring secure access control. WebSockets Integration: Ensured real-time data exchange between the frontend and the robot, improving response times and interaction reliability.

Supervisor

Supervisor

Dr. Isuru Nawinne

Our Team

Team Member

P.A.WICKRAMARACHCHI

E/20/434

Team Member

A.I.FERNANDO

E/20/100

Team Member

PATHIRAGE R.S

E/20/280

Team Member

MALINTHA K.M.K

E/20/243

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