Multi-Agent Quadrotor Hardware and Simulation

Designed and built a crash-resistant quadrotor platform to support multi-agent robotics research in BYU's MAGICC Lab. My work included parametric CAD, ROS 2 and Gazebo simulation, and integration of an AI-agent interface for natural-language control. The project demonstrates strength in robotics systems, mechanical design, prototyping, and software integration.

Role
Research Assistant
Team
BYU MAGICC Lab
Duration
May 2025 - August 2025
Outcome
Delivered a crash-resistant quadrotor platform and simulation stack for multi-agent and AI-agent robotics research.
Core Tools
Onshape CAD, ROS 2, Gazebo, PX4, Docker, LangChain/LangGraph
View on GitHub Project Website
3D-printed quadrotor platform and protective spherical cage developed for robotics research.

Overview

Created a 3D-printed, crash-resistant, LLM-enabled quadrotor with high customizability to provide a platform for multi-agent coordination and AI-agent research within the MAGICC Lab.

Key Contributions

  • Designed parametric CAD parts for a 3D-printed quadrotor and spherical protection cage
  • Created Gazebo simulations of multiple quadrotors using ROS 2 communication and control
  • Integrated an AI agent with ROS 2 for natural-language control of multi-agent simulations

Timeline

  • Duration: May 2025 - August 2025
  • Total time: Approximately 300 hours
  • Time commitment: About 30 hours per week for 12 weeks

Results

Custom Quadrotor

CAD model and assembled quadrotor
Spherical protection cage: CAD model and physical assembly

Multi-Agent Coordination

Keyboard input commands

Waypoint following

AI Agent Integration

Natural language command processing

Technical Skills