Linear-quadratic regulator rapidly exploring random tree

Linear-quadratic regulator rapidly exploring random tree (LQR-RRT) is a sampling based algorithm for kinodynamic planning.

The method is an extension of the rapidly exploring random tree, a widely used approach to motion planning.

[1] A set of differential equations forms a physics engine which maps the control input to the state space of the system.

These signals are determined and constantly updated with the receding horizon strategy, also known as model predictive control (MPC).

[3] In 2016 the algorithm was listed in a survey of control techniques for autonomous vehicles[6] and was adapted by other academic robotics teams like University of Florida for building experimental path planners.

[8][9][10][11] It is currently part of the Relative Satellite Swarming and Robotic Maneuvering (ReSWARM) experiments taking place at the International Space Station since April 2021 starting with expeditions 65 and 66.