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Joon ParkWoolin JungDanny KawieckiDrew Stadelman
Published

AI-based Maze Solving & Load Carrying Robot - UIUC ME461

This project was conducted as part of the final project for the course ME461, which was held at the University of Illinois Urbana-Champaign.

IntermediateShowcase (no instructions)126
AI-based Maze Solving & Load Carrying Robot - UIUC ME461

Things used in this project

Hardware components

LAUNCHXL-F28379D C2000 Delfino LaunchPad
Texas Instruments LAUNCHXL-F28379D C2000 Delfino LaunchPad
×1
Servo Module (Generic)
×1

Software apps and online services

Code Composer Studio
Texas Instruments Code Composer Studio
LabVIEW Community Edition
LabVIEW Community Edition
OpenAI API
Fusion
Autodesk Fusion

Hand tools and fabrication machines

3D Printer (generic)
3D Printer (generic)

Story

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Custom parts and enclosures

Robot Mounting Plate with Servo Housing

This plate attaches to the robot and also allows for a HS-311 Servo Motor to be inserted into a housing module.

Sketchfab still processing.

Bucket Base with Connecting Rod to Circular Servo Flange

Connects the servo to the bucket base and allows the base to rotate 90 degrees, thus releasing the payload

Sketchfab still processing.

Bucket/Chute Structure with Robot Mounting Attachment

This acts as a bucket to hold the payload, it also is able to be mounted/attached to the robot due to the fin-like extension that was designed with it.

Sketchfab still processing.

Code

Maze Solver (LLM vs A* algorithm) and json file generation

This repository contains all the code used in the project. This ranges from scripts to generate training data, format and clean the data, use the fine tuned chatGPT LLM to solve mazes, use A* algorithm to solve mazes, and test the LLM's performance across a batch of mazes. Test cases or mazes are also included.

Credits

Joon Park
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Woolin Jung
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Danny Kawiecki
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Drew Stadelman
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