CYNET.ai

Team CYNET.ai - SubT Challenge Qualifier

Team CYNET.ai was selected by DARPA (the Defense Advanced Research Projects Agency) as a qualifier in its ground-breaking SubTerranean Challenge (SubT). SubT is a multi-million dollar competition that will task teams of robots with autonomous exploration deep beneath the surface of the Earth.

After a few months of developing software for the qualification process Team CYNET.ai was one of the only 8 teams around the world chosen to continue through the virtual track of the competition. Other competitors include NASA, CalTech, MIT, Carnegie Mellon, Georgia Tech and several other robotics companies. Most of them are being funded by DARPA. Team CYNET is self-funded and doesn't benefit from the availability of university labs.

The first round (Tunnel Circuit) didn't go very well but it was a good learning experience for us. In the second round (Urban Circuit) we scored more points and now we're really looking forward to improve our systems for the Cave Circuit.

Want to be a part of the team’s success? The SubT Challenge is a multi-year, complex endeavour. Team CYNET is looking to form partnerships and welcomes any kind of financial and equipment assistance in order to compete with the major institutional teams. Sponsors will get exposure in our media, demos, videos and tech articles.

The DARPA Subterranean Challenge aims to develop innovative technologies that would augment operations underground. The SubT Challenge will explore new approaches to rapidly map, navigate, search, and exploit complex underground environments, including human-made tunnel systems, urban underground, and natural cave networks.
Check out more details about SubT.

Tunnel Systems (2019)

Human-made tunnel systems, like mines. Current stage of the competition.

Subterranean Challenge underground robots

Urban Underground (2020)

Urban and municipal underground infrastructure, like subway stations.

Cave Networks (2020)

Naturally formed networks of tunnels and chambers, with rugged terrain.

Programming the next generation of
autonomous underground robots

Team CYNET.ai is using advanced technologies in the field of robotics, computer vision and deep learning in order to deploy a swarm of robots through the current tunnel environment. These robots move auonomously, they build a map of the unknown environment, exmplore it, find artifacts, calculate their location, and then communicate their findings back to the Base Station.

System Components

Our robotics software project has three main components:

Mapping and localization

The robots don't know the environment. As they explore it, they must both create a dynamic map and calculate their position by sensor fusion.
Robot motion control

It involves both optimized path planning through the tunnel structure (as battery life is limited) and a PID controller to steer through the narrow passages.
Artifact detection

Images from the onboard camera pass through a convolutional neural network to identify and localize known objects.