Max’s journey introduces LQRax, a JAX-native LQR solver, which exemplifies the growing JAX robotics ecosystem that includes tools like Brax, MJX, and JaxSim, highlighting the benefits of JAX for computational efficiency in optimal control and simulation, and for seamlessly integrating model-based and learning-based approaches.
A roboticist’s journey with JAX: Finding efficiency in optimal control and simulation
Related Posts
Artisanal Web Development
On our last episode of Static Feedback, I spoke with Joost van der Schee about ‘Artisanal Web Development’,…
Creating Session Counts
Current status Shortly after completing the Cloud Resume Challenge I decided to revisit it and choose a selection…
Easy FunctionGemma finetuning with Tunix on Google TPUs
Finetuning the FunctionGemma model is made fast and easy using the lightweight JAX-based Tunix library on Google TPUs,…