Entry Date:
July 1, 2024

MIT Astrodynamics, Space Robotics, and Controls Lab (ARCLab)

Principal Investigator Richard Linares

Project Start Date July 2018


The MIT Astrodynamics, Space Robotics, and Controls Lab (ARCLab) works at the intersection of astrodynamics, autonomy, and controls to further space exploration.

The ARCLab, led by Prof. Richard Linares, is a research group in the MIT Department of Aeronautics and Astronautics. Founded in 2018, the group’s research topics include astrodynamics, space situational awareness and space traffic management, satellite guidance and navigation, estimation and controls, reinforcement learning, and optimal control.

ARCLab researchers are currently pursuing projects spanning astrodynamics, autonomy, and controls.

Spaceflight is entering a period of renaissance, with considerable change in the perception of what humanity’s role in space will be. New proposed satellite mega-constellations could revolutionize the telecommunication industry by providing complete global internet coverage. However, the current space infrastructure is not capable of handling such a dramatic increase in the number of active satellites. Therefore, ARCLab conducts critical research and develops new solutions for the problems of Space Traffic Management (STM) and Space Situational Awareness (SSA).

Conversely, the technologies that are revolutionizing near-Earth spaceflight will provide new opportunities for deep space exploration. Future science-driven interplanetary missions and/or missions to Lagrangian points and asteroids will require advanced guidance and navigation algorithms that are able to adapt to more demanding mission requirements. For example, future missions to asteroids and comets will require that the spacecraft be able to autonomously navigate in uncertain dynamical environments by executing a precise sequence of maneuvers (e.g. hovering, landing, touch-and-go) based on information collected during the close-proximity operations. These missions will require approaches for landing at selected locations with pinpoint accuracy while autonomously flying fuel-efficient trajectories. Our recent work in this area has developed new methodologies for solving these problems. For more information please review our publications page.