Understand the release without assuming compatibility

The Open Robotics release announcement identifies Lyrical as an LTS release supported until May 2031. It lists Ubuntu 26.04 on amd64 and arm64 among Tier 1 platforms. It also describes executor, Python async and data-buffer changes. These are reasons to inspect the release notes against your own workload, rather than treating an upgrade as an automatic performance improvement.

A distribution’s support tier does not guarantee support for your camera driver, GPU runtime, vendor SDK, middleware implementation or controller. NVIDIA’s September Isaac ROS announcement describes its own platform support. Check each vendor’s exact release matrix instead of combining independent support statements into an assumed compatible stack. Pin the versions you actually test.

Create a dependency inventory you can act on

List the operating system, architecture, ROS distribution, RMW implementation, compiler, Python version and relevant hardware runtimes. Then inventory packages, custom messages, controller plugins, launch files and vendor libraries. Record the source repository and installed version for each important dependency, including anything built outside your workspace.

Classify dependencies as verified compatible, requiring changes or not yet verified. An unknown should stay visible as an unknown. Do not make a production robot the first place you discover an unavailable binary or a changed configuration format. Keep a reproducible copy of the existing environment and a separate migration branch.

  • Operating system and CPU architecture, including deployed edge hardware.
  • ROS packages, RMW, custom messages and third-party SDK versions.
  • URDF, controller configuration, launch files and parameter files.
  • GPU or accelerator runtime and the packages that depend on it.
  • A documented route back to the existing tested environment.

Capture a baseline before changing the stack

Pick representative tasks and record the existing behavior under stated conditions. Useful observations include topic rates, message sizes, timestamp behavior, transform availability, startup sequence, controller response, resource use and recording throughput. Use the same input data and configuration when comparing the migration where practical.

Record what counts as a failure before running the comparison. A node that starts without an error is not proof that the robot behaves correctly. Include delayed messages, unavailable sensors, restarts and invalid configuration where these are relevant to the system. Separate correctness checks from performance measurements so a faster result does not hide changed behavior.

Test the interfaces where migrations become expensive

Inspect custom message and buffer assumptions, parameter handling, composition, callback execution and controller interfaces. Review the migration notes for the packages you use, not only the core distribution notes. If you adopt a new executor or data-transfer path, measure its behavior in your workload rather than copying a headline improvement into your own results.

For transforms, check units, frame names, direction and rotation conventions. Our quaternion converter can help inspect a single orientation, but a correct quaternion does not validate an entire transform tree. For recordings, compare expected data volume with actual bags and verify that playback supports the debugging task you need. These small checks help isolate an interface problem before it is mistaken for an algorithm problem.

Roll out with evidence and a rollback plan

Move from a reproducible build to replayed data, then simulation or a controlled hardware test appropriate to your system. Define which checks must pass before the next stage. Preserve logs and configuration with the result so another engineer can reproduce the observation. Hardware changes and software changes are easier to diagnose when they are evaluated separately.

Keep the previous tested environment recoverable and document the rollback procedure before deployment. After a successful migration, publish a concise internal report: what changed, why, how it was tested and what remains uncertain. For candidates, a non-confidential version of that reasoning can demonstrate systems judgment more clearly than simply listing the newest distribution on a résumé.