R.O.A.M

Group #14 - Summer 2025 Senior Design Project

Team Members:
Claire Persinger, Ethan Robotham, Daniel Claassen, Nathan Little

R.O.A.M. is an autonomous robot designed to detect and report discarded and salvageable items found near residential sidewalks. It aims to reduce waste by categorizing objects into trash and treasure using a trained object classification model, then uploading the information to a website for local residents to access before waste collection takes place.

Key Features & Components

• Object Detection & Classification: Uses camera and LiDAR to identify objects.
• Autonomous Navigation: LiDAR helps guide the robot while it patrols sidewalks.
• Data Reporting: Objects are classified and location data sent via a SIM module.
• Machine Learning: Uses OpenCV to train a classification model.

Project Inspiration & Goals

This project was inspired by frequent sightings of discarded but usable items left on sidewalks.

• Reduces landfill waste by identifying salvageable items.
• Helps keep neighborhoods clean.
• Operates as a three-wheeled autonomous robot.

Technology & Implementation

• LiDAR: Tracks sidewalk boundaries.
• Camera: Captures images for classification.
• GPS Module: Sends object coordinates.
• Website: Displays classified items for public use.

Click here to see what R.O.A.M. is doing!