A roboticist’s journey with JAX: Finding efficiency in optimal control and simulation

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 simulatio…


This content originally appeared on Google Developers Blog and was authored by Google Developers Blog

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.


This content originally appeared on Google Developers Blog and was authored by Google Developers Blog


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Google Developers Blog | Sciencx (2025-07-29T19:44:49+00:00) A roboticist’s journey with JAX: Finding efficiency in optimal control and simulation. Retrieved from https://www.scien.cx/2025/07/29/a-roboticists-journey-with-jax-finding-efficiency-in-optimal-control-and-simulation/

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" » A roboticist’s journey with JAX: Finding efficiency in optimal control and simulation." Google Developers Blog | Sciencx - Tuesday July 29, 2025, https://www.scien.cx/2025/07/29/a-roboticists-journey-with-jax-finding-efficiency-in-optimal-control-and-simulation/
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