An experimental design of a robotic delivery company

• Main Author: Foo, Melvin Maw Qing
• Other Authors: Kong Wai-Kin, Adams
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science
• Online Access: https://hdl.handle.net/10356/175275
• Institution: Nanyang Technological University

This FYP focuses on the development of delivery robots for a startup company. The objective of the project is for a student who wants to establish his/her company after graduation. The project created a robotic delivery company and piloted a Robotic Delivery as a service (DaaS) on the NTU campus. The startup aims to reduce cost for users, increase profitability for businesses and improve quality of life for logistics workers. This report details technical and business details of the startup. Listed below are requirements of the project: 1. This project must be IT-related. 2. A sound business plan is essential, or the project will be useful for charity organisations. 3. A prototype must be developed. This project investigates the development of a pedestrian autonomous vehicle specifically designed for food delivery in a “campus” environment. The startup designed both Hardware and Software. The hardware includes the robot chassis and electrical components. While the software encompasses robotic, fleet management, teleoperation, and AI self-driving software tailored for autonomous navigation and food delivery tasks. This project aims to find out if one can create a reliable and efficient autonomous vehicle that can navigate safely among pedestrians, deliver food orders accurately and timely, and optimise food delivery in a campus setting. The information for this project was collected through extensive research on existing autonomous vehicle technologies, pedestrian tracking systems, and food delivery logistics. The company employed rapid development methodology - developing custom navigation software, obstacle avoidance, fleet management software, and AI-based decision-making algorithms. The developed pedestrian based autonomous vehicle successfully navigates predefined routes on the campus, avoids obstacles such as pedestrians and static objects, and delivers food orders to designated locations accurately and within specified time frames. The software systems work seamlessly together to ensure efficient operation and reliable performance. The project demonstrates the feasibility and effectiveness of using autonomous vehicles for campus food delivery. Recommendations for future work include enhancing the vehicle's AI capabilities for real-time decision-making, focusing on software efforts and pivoting the company to focus on operations.