StanfordQuadruped VS lucene-grep

I just pulled up the cad. The robot is open source so there is a good amount of documentation. The leg design is the same as most quadruped robots use 3 revolute joints. While the pupper does have a 4 bar linkage for the knee, I'm fairly certain that the link lengths mean its just a parallelogram. This leg design is simple enough that your unlikely to find a research paper covering it. Here is the code where they do the kinematics: https://github.com/stanfordroboticsclub/StanfordQuadruped/blob/master/pupper/Kinematics.py

- Graal native images are real. These boast a far lower startup overhead and much lower steady state memory usage for simpler applications.

Probably my counterexample of choice is this: https://github.com/dainiusjocas/lucene-grep - it uses Lucene, probably the best search library (core of Elasticsearch, Solr, most websites), which is notoriously not simple code to implement grep-like functionality. In simple cases, they demonstrate a 30ms whole process runtime with no more than 32MB of RAM used (which looks suspiciously like a default).

The JVM is fast becoming a bit like Postgres... one of those 'second best at everything' pieces of tech.

Here goes: https://github.com/dainiusjocas/lucene-grep/issues/84

I realize some relatively obscure Finnish stemmer and Lucene with GraalVM aren't exactly a common use case. I did some testing and provided my use case. I certainly have much English language content to search with using lucene-grep. So, thank you for making it!