Small Scale Autonomous Vehicles – Small Scale Autonomous Vehicles – Senior Design/Capstone Project UCF 2024

Our Goal

Our primary goal is to build two small-scale autonomous race cars capable of competitively navigating an indoor racetrack in the presence of other race cars with the same goal

Project Overview

Mechanical

The vehicle will feature a lightweight and durable chassis optimized for high-speed racing. The chassis is made from materials that provide an ideal balance between strength and weight, enhancing speed and handling. Aerodynamics will be a key focus, reducing drag to achieve higher top speeds and improving overall efficiency. The drivetrain is designed for rapid acceleration and high speeds, while the finely tuned suspension system ensures optimal handling through various cornering scenarios, allowing the vehicle to adapt to a variety of racing conditions.

Hardware

The vehicle will be equipped with advanced sensor systems to support autonomous operation. Key sensors include LiDAR for proximity sensing and collision avoidance, an RGBD camera to capture color and depth information for enhanced environmental awareness, and an Inertial Measurement Unit (IMU) for precise orientation and motion data. These sensors work together to feed data into the SLAM algorithm for mapping and navigation. The vehicle will also have an external RC control system for manual operation and onboard displays to monitor critical metrics like power distribution and speed during testing and races.

Software

The vehicle’s software will manage autonomous navigation, path planning, and real-time decision-making. SLAM algorithms will use data from the sensor suite to simultaneously create a map of the environment and localize the vehicle within it, enabling dynamic obstacle avoidance and real-time path adjustments. Path-following algorithms will calculate the optimal trajectory based on the vehicle’s dynamic capabilities, adjusting speed and steering in real-time. All software systems, including ROS, SLAM, and path planning, will run on a high-performance computer with a GPU, ensuring low-latency processing for fast and accurate decision-making during races.

Motivation

Cutting-edge Challenge

Autonomous racing combines various complex domains such as computer vision, real-time decision-making, and control systems. The fast-paced environment of a race demands the highest level of precision and optimization, which pushes us to challenge our technical skills and innovate.

Real-World Applications

Autonomous vehicles are shaping the future of transportation and robotics. By working on this project, we are contributing to the development of technologies that have the potential to revolutionize industries.

Interdisciplinary Collaboration and Professional Growth

This project allows us to collaborate across disciplines, combining expertise from electrical, mechanical, computer engineering, and computer science. Practicing this kind of complex collaboration now, puts us a step ahead in preparing to work in the robotics industry.

Community Contribution

One of our goals is to make this project available for anyone to use and learn from. We want to contribute to bridging the gap of knowledge when it comes to autonomous vehicles. We aim to create simplified detailed step-by-step instructions on how to replicate our final product.