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iLQR · Bharath2

A Numba-accelerated iLQR implementation with state and input constraints.

mpcilqrilqgnonlinear-optimizationtrajectory-optimization
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iLQR · Bharath2 resource page screenshot
Resource screenshot · captured 2026-10-08 · visually reviewed

Overview

A Numba-accelerated iLQR implementation with state and input constraints.

Publisher summary: “iterative Linear Quadratic Regulator with support for constraints on input and state variables via barrier functions—Numba-accelerated.”

Use its repository to inspect the implementation, documentation and supported workflows. This directory record identifies the maintainer, code license and related resources; it does not claim that the project has been installed or tested on your robot.

Project information

Maintainer
Bharath2
Primary language
Python
Repository code license
BSD-2-Clause
Model-weight license
Not recorded
Dataset license
Not recorded
Hardware design license
Not recorded
Maintenance
Not archived in the last recorded metadata
Last observed repository push
2025-05-06

Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.

Documentation sections

  • iLQR
  • Usage
  • Construting Dynamics
  • params
  • Construting Cost
  • iLQR

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