vedantnair

This is great feedback. Thank you.

> Wow, these people don't know how to filter git log by directory? This is pretty messed up, no wonder that git does not work to them.

Hmm... good point. Would you say that a directory per device is the best way to manage robot config? Have you felt that non-technical users are comfortable with this? Curious what your experience has been like.

> oh! This was a strawman argument to motivate their SAAS. Still, it's a pretty weak one.

I don't think this is a strawman argument. This is a problem we've heard from real robotics teams as they scale their fleets. I did my best not to shill. I'd like to think that reserving one sentence at the end of the blog is acceptable.

Still, I'd love to hear where you think the arguments are weak so I can reconsider them. Thanks again for reading. I appreciate it!

The problem with using Git as the backbone of your robotics config management is that Git is more like a datastore, where you really need a database.

As you scale, this affects your ability to scale RobotOps, to stand up other fleet management tooling, and to provide the security/access controls your customers need.

This is Chapter 2 of Config Wars! Today, we’re diving into JSON Schema.

JSON Schema was popularized through its use in validating API requests in the OpenAPI format. Since JSON is universal, it’s quickly become the largest, most well supported schema validation ecosystem.

It boasts a strong community of third-party and code-generation validation libraries that we’ll discuss.

It can natively struggle with overrides (you’ll have to use a templating engine like Jinja), but thankfully, we’ve made this seamless with Miru’s config management tool.

In this five-part series, we'll be deep diving into why schemas are so important for scaling a robotics configuration management system and battling it out between different schema formats.

By the end of the series, you'll be an expert at what schemas are best for what use case and their respective tradeoffs. This will give you and your team the confidence to choose a schema that's best for your fleet.

In this chapter, we'll be introducing schemas: why they're powerful, what they are used for, and what we care about when choosing a schema.

Choosing the right schema language is an important part of scaling software infrastructure for a growing robotic fleet.

Unfortunately, most robotics teams aren't well-versed in the different features and functionalities of each language, which can lead to short-term optimizations.

In this blog, we’ll give you all the information you need to choose the right schema for your production fleet. We’ll walk through what a schema language is, why they’re useful, our main criteria when choosing a schema, and finally, a few options for popular schemas in robotics.

Managing configs is a pesky infrastructure problem that slows down scaling robotics fleets.

A single robot can have thousands of configuration parameters, many of which are custom, based on factors such as the customer site, hardware version, etc. This makes it difficult to manage which configs belong on which robot, version them globally (while maintaining sanity for local edits), and deploy them to your device.

In this blog, I wrote about the challenges teams have faced with config management and how we’ve designed Miru to solve them.

Another Figure demo, this time showing how they trained the humanoid gait with RL.

We all know to take robotics demos with a grain of salt, but I still think it's clear that RL is the path forward in robotics locomotion.

More compute, more sim, more robots!