To apply Reinforcement Learning techniques in training Trossen Aloha Stationary Robot Arms to autonomously perform complex, unstructured tasks. This project aims to enhance the adaptability and efficiency of robotic systems in dynamic environments, supporting the company's goal of developing intelligent automation solutions through advanced machine learning methods.
Semester of Project:
Spring 2025
Team Photo:
Team Poster:
Problem Statement/Summary:
Using Reinforcement Learning, this project trains Trossen ALOHA robot arms to perform complex, unstructured tasks autonomously, bridging the gap between simulation and real-world execution through careful data collection, testing, and system refinement.
MS Teams Meeting Link:
https://teams.microsoft.com/l/meetup-join/19%3ameeting_OTA0YjM4MDQtYmFlNS00NGFiLWIyMmQtNjM1MTIxN2NmZDg4%40thread.v2/0?context=%7b%22Tid%22%3a%224130bd39-7c53-419c-b1e5-8758d6d63f21%22%2c%22Oid%22%3a%22891f2e94-5958-41ee-b930-85bd75986c1a%22%7d
Project Department:
SOET
Project Presentation Video Embed Code:
Project Sponsor Website:
https://packaging-systems.com
Project Sponsor:
packingsystems
Team Contact:
Andrew Watts - ajwatts@purdue.edu - 206-9193-7137