In Modular Space Robotics, modules self-assemble while in orbit to create larger satellites for specific missions. Modular satellites have the potential to reduce mission costs (small satellites are cheaper to launch), increase reliability, and enable on-orbit repair and refueling. Each of the modules has its load of sensors, fuel and attitude control actuators (thrusters). Assembled modules therefore have redundant sensor and actuation capabilities. By fusing sensor data, the modular satellites can follow its trajectory more precisely and smart thruster activation can help save fuel.
The challenge is to figure out how to control such a self-assembled robot to minimize fuel consumption while balancing fuel distribution and improve trajectory following. To this end, Toglia et al. propose a cooperative controller where one of the modules, with information about the configuration of all other modules, is responsible for computing an optimal control schema. An extended Kalman-Bucy Filter is used to implement sensor fusion.
The cooperative controller was compared to an independent controller where each module attempts to follow its own trajectory while minimizing its own fuel usage and trajectory errors. Results from simulation and reality show that the cooperative controller can save significant amounts of fuel, up to 43% in one experiment, while making the trajectories more precise.
Experiments in reality were performed with two satellites using the MIT Field and Space Robotics Laboratory Free-Flying Space Robot Test Bed shown below.