Recently, we released our ROS whitepaper and continued work toward our goal of a fully autonomous robot. We hope you’ve had time to digest that whitepaper because we’re back with another one about computer vision! This year, we focused on making our robot more environment-aware by developing more robust sensing and inference systems.
Are green lights and retroreflective tape dead?
Neural net all the things
Introducing the dramatic pause Zebra Positioning System™
Our vision for the future of, well, vision!
Data for everyone!*
Thank you to our wonderful mentors and students who were instrumental to our progress this year. And, as always, thank you to the NCSSM Foundation, NVIDIA, Analog Devices International, Stereolabs, AWS: Robomaker, Overleaf, and our other wonderful sponsors who make our work possible.
*No, really! We’re actually making public our dataset that we used to train our object detection model this season, which consists of images with approximately 15,000 labeled objects. By doing this, we hope to foster a culture of open data in the FRC community, enabling all teams to innovate, develop, and use machine learning technologies.
NCSSM Ryden AI Program - North Carolina School of Science and Mathematics – The Ryden Program for Innovation and Leadership in Artificial Intelligence
The Ryden Program’s goal is to educate the leaders of the future about AI so that they understand this powerful technology’s merits and the ethical considerations it raises.