Fair haha... if you ever want the filter without the middleware, fusioncore_core is pure C++17 with zero ROS dependency. The ROS wrapper is thin on purpose. And if you're ever dealing with sensor fusion headaches on a project, feel free to reach out... happy to help regardless of stack. :)
Fair point about the README... yeah, I did use Claude to help with the docs. But just to be clear, I’m not using OpenClaw or any other automated tools. FusionCore is a legit package: it’s available via apt, and the code’s up on GitHub. The filter and benchmarking work are my own. If you want to dig into the implementation, the core math is in ukf.cpp and fusioncore.cpp.
As for WOLF... it’s actually a really interesting framework, so credit where it’s due. That said, it’s built around a different philosophy. It’s a general-purpose factor graph system, while FusionCore is more opinionated and tuned specifically for GPS/IMU/wheel-based outdoor robotics.
If you’ve got a dataset you’d like me to run FusionCore on, send it over... I’m happy to share results. That might be a more useful way to compare them.
Why would it matter that it’s AI generated? Are you allergic?
It has almost 200 commits since mid March. It’s AI generated. Determining that took me 2 minutes. The high order bit here is actually whether it is of high quality.
If it is high quality (I didn’t check) and it’s honest about its provenance, the way it was made is immaterial.
Appreciate it. If you get a chance to take a look, the benchmark methodology and the RL comparison configs are all in the benchmarks/ folder, so you should be able to reproduce the results pretty easily.
I’ve already had six testers validate things across a range of environments—agricultural fields, open spaces, tunnels, underpasses, and even urban canyons with brief GPS dropouts. In those kinds of scenarios, FusionCore’s gating really stands out as a strength.
I hate to say this, but this submissions readme seems obviously AI generated.
As for WOLF... it’s actually a really interesting framework, so credit where it’s due. That said, it’s built around a different philosophy. It’s a general-purpose factor graph system, while FusionCore is more opinionated and tuned specifically for GPS/IMU/wheel-based outdoor robotics.
If you’ve got a dataset you’d like me to run FusionCore on, send it over... I’m happy to share results. That might be a more useful way to compare them.
It has almost 200 commits since mid March. It’s AI generated. Determining that took me 2 minutes. The high order bit here is actually whether it is of high quality.
If it is high quality (I didn’t check) and it’s honest about its provenance, the way it was made is immaterial.
I’ve already had six testers validate things across a range of environments—agricultural fields, open spaces, tunnels, underpasses, and even urban canyons with brief GPS dropouts. In those kinds of scenarios, FusionCore’s gating really stands out as a strength.