The problem is not that there is no standard -- there is, it's called ROS. The problem is that manufacturers are not interested in opening their robots up to that degree.
Also, REST is a terrible idea for interacting with robots. REST is call-response based. But with Robots a pub/sub (like ROS or MQTT) or a blackboard data architecture (like what we used in Transitive Robotics) is much more efficient and natural.
On ROS being the standard — you're right that ROS exists,
but adoption outside research/academia is still fragmented.
Boston Dynamics, Universal Robots, and most industrial arms
don't natively speak ROS — teams still write glue code.
RoboAPI is trying to be that glue as a managed layer rather
than a DIY problem.
On REST being wrong for robots — completely agree on the
pub/sub point. REST is the entry point for developer
familiarity but RoboAPI already has WebSocket streaming for
telemetry. The next step is moving commands to pub/sub too.
Interesting that you mention Transitive Robotics — the
blackboard pattern is something I've been thinking about
for the fleet layer.
What would the ideal architecture look like from your
experience? MQTT for commands, WebSocket for telemetry,
REST only for configuration?
Foxglove is not the only name in town. There are many, Transitive Robotics, the company I'm building is one of them. Different from Foxglove we are much more focused on live-remote monitoring and control, e.g., we have a pretty popular remote teleoperation module: https://transitiverobotics.com/caps/transitive-robotics/remo...
You can find all the other modules we're currently offering here: https://transitiverobotics.com/caps/
The platform itself is and remains open-source.
We are thrilled to announce a new major version of Transitive, the open-source framework for full-stack robotics. Version 2.0 adds significant new integrations and features: storage of historic and time-series data in ClickHouse, visualization in Grafana, and custom alerting via Alertmanager. Some of our capabilities, like the free Health Monitoring capability, already use these features, providing significant added value to robotics companies with growing fleets.
This is absolutely awesome. Thanks for sharing! I would love to chat more with you. For context: we make a remote teleoperation solution for robotics. It's mostly used for mobile robots, but we've been getting a lot of inquiries regarding teleoperation for manipulation, so I've been learning more about this, in particular regarding the question of speed. I really appreciate these results!
"the funding all these startups are getting should allow them to scale their methods 10x-100x.." .. "Therefore, we might soon see a ChatGPT moment in robotics" -- I don't think so and no, the second statement is NOT entailed by the first. Why would it? Because 100 is a big number? Do you have any idea how much more data LLM needed to be trained for a GPT3 level compared to the data available for robot training right now, and how low dimensional the space is in which LLMs operate compared to robots?
"My intuition is there's 40% chance we will see it this year" -- again, why? Don't you realize that people have been working in robotics for 65 years, and these people don't live under a rock either. They knew about GPT3 because 2023. So why is it NOW less then 10 month you think that this breakthrough will happen?
I think it’s a combination of simulation, YouTube videos, and specially recorded training footage. The last one is expensive, but given the funding these startups receive, I’m pretty sure they can scale their RL methods at least 10x.
How can you seriously state that as a positive? Are you trying to exemplify the new AI-patent-generation-mill? No one in their right mind can expect a person to make 10 meaningful inventions in 4 days.
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