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anassinator avatar

anassinator/ilqr

0
View on GitHub↗
423 stars·84 forks·Python·GPL-3.0·7 views

Ilqr

Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models

Features

  • Motion Planning and Control - Iterative linear quadratic regulator with differentiable dynamics.
  • Planning and Control - Iterative linear quadratic regulator with differentiable dynamics.

Star history

Star history chart for anassinator/ilqrStar history chart for anassinator/ilqr

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

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Frequently asked questions

What does anassinator/ilqr do?

Iterative Linear Quadratic Regulator with auto-differentiatiable dynamics models

What are the main features of anassinator/ilqr?

The main features of anassinator/ilqr are: Motion Planning and Control, Planning and Control.

What are some open-source alternatives to anassinator/ilqr?

Open-source alternatives to anassinator/ilqr include: alexliniger/mpcc — Model Predictive Contouring Controller (MPCC) for Autonomous Racing. alphaville/optimization-engine — Nonconvex embedded optimization: code generation for fast real-time optimization + ROS support. astuff/pacmod — A ROS driver for the AutonomouStuff PACMod drive-by-wire system. atsushisakai/hybridastartrailer. casadi/casadi — CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse… acado/acado — ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It…

Open-source alternatives to Ilqr

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  • acado/acadoacado avatar

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    ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization.

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See all 23 alternatives to Ilqr
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