AI agents can now debug robotics data for you.
In October at
#ROSCon and November at
#PX4 Dev Summit, I demoed an AI agent debugging a robot log end-to-end for the first time. I got a healthy mixture of excitement and skepticism from the audiences. Back then, “agents” was still a term mostly being used by AI investors, but internally the results had surprised us enough to start testing with customers. Since then, foundation models have gone through another step change in capability.
For several decades in robotics, the debugging loop has been the same. A robot fails, you pull the logs, replay sensor data, and spend hours trying to figure out what happened. While you’re doing that, another robot fails for a different reason. This has quietly been one of the biggest bottlenecks holding the industry back. If your robots are constantly failing and it takes hours to investigate each issue, you can’t scale up your deployments.
At
@roboto_ai, we've been building the foundation to change this. Instead of manually digging through logs, you can ask what happened and have the system investigate, explain, and pull up the relevant data. I recorded a short video of me debugging a PX4 Autopilot drone flight using our new AI Chat interface.
Customers are already using this to automate review and integrate with their internal systems. We think this will finally let robotics teams scale the way software teams do.
#robotics #data #agents #ros #px4