Multimodal UAV Collision Avoidance Detection & Tracking

Drone Based transportation system.

If you have excellent programming skills and some knowledge of machine learning consider this exciting project ! 

Project description

In recent decades, the world has seen an unprecedented growth and improvement of unmanned aerial vehicle  technologies ( UAV, also called drones) with a wide range of applications in transportation, search and rescue, security surveillance, communication relays, filming, entertainment, and monitoring. The existing methods are not designed to effectively handle security and privacy related issues or a wide range of weather conditions. 

Project outcome

This project aims to develop a novel, multi-modal obstacle sense and tracking system. 

Project details

Timing, eligibility and other details
Length of commitment Longer than a semester (6-9 months)
Start time Summer (May/June of 2022)Fall (August /September 2022)
In-person, remote, or hybrid? Hybrid project
Level of collaboration Small group project (2-3 students)
Benefits Satisfying independent study/supervised research requirement 
Who is eligible Junior and senior undergraduate students with prerequisite skills & courses in Python, Intro to ML/Intro to AI, or related courses

Project mentor

Sreyasee Das Bhattacharjee

Assistant Professor of Research & Training

Computer Science & Engineering

Phone: (716) 645-4769

Email: sreyasee@buffalo.edu

Start the project

  1. Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
  2. After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.) 
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Preparation activities

The specific preparation activities for this project will be customized through discussions between you and your project mentor. Please be sure to ask them for the instructions to complete the required preparation activities.

Keywords

Computer Science & Engineering