Firefly combines deep learning, computer vision, and advanced robotics to explore complex indoor spaces without a human pilot.
Our state-of-the-art algorithms can construct high-resolution, photo-realistic 3D maps of indoor environments in real-time.
We’ve also built an end-to-end analytics engine that uses AI to uncover meaning from these maps and any other sensor data we gather during flight – ultimately providing critical business insights to end users.
Finally, we do all of this using low-cost sensing and processing hardware, making our drone far more capable but also far more cost-effective than existing drone solutions.
Firefly dramatically speeds up the creation of detailed 3D maps of indoor spaces through our drone’s onboard, real-time mapping technology.
Firefly replaces expensive and inefficient manual inspections by autonomously identifying defects in critical components of power plants, mines, and factories.
Firefly reduces huge budget overruns by navigating a building under construction without a human pilot and using AI to track progress in critical areas.
Firefly saves lives of both first responders and victims by autonomously carrying out search-and-rescue missions in dangerous or hard-to-reach places.
We’re Stanford students building the future of intelligent machines. We have a deep research background in aerial robotics, computer vision, and machine learning.
We’re passionate about building on academic research to make an impact, and we’re especially excited about Firefly because we think it’s about time we started sending robots, rather than people, into dangerous places.
Research experience from:
We’re currently working on setting up pilots to demonstrate our technology. If you think you might have a use case for us, please get in touch!