is a university-driven research project. The first version was developed by Perez et al. at the Massachusetts Institute of Technology in 2012 in the AI laboratory. In 2016 the algorithm was listed in a survey of control techniques for autonomous vehicles and was adapted by other academic robotics teams like University of Florida for building experimental path planners. In 2018, the algorithm was included in the Pythonrobotics library. The algorithm is currently being tested on the Astrobee, a six degree of freedom (DOF) free-flyer with a 3 DOF robotic arm in the International Space Station. 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. Future experiments will entail physical manipulation of objects to further validate the on-orbit assembly demonstration, consideration of physical objects for real-time mapping and collision avoidance, and bringing the information-theoretic framework to a greater set of uncertain robots. References External Links MIT ARCLab Microgavity Research A Python Code Collection of Robotics Algorithms LQR-RRT* code and visualization PythonRobotics LQR-RRT* code LQR-RRT* presentation Optimal control Search algorithms