A Swarm-Driven Solution for Space Debris Removal: Inspection, Capturing, and Controlled De-Orbiting

The increase in number of the space debris has emphasized the need for effective concepts and technologies for active debris removal, minimizing the risk of collisions with operational satellites. The existing approaches mainly rely on single-satellite service providers, which offer certain advantages but also come with several limitations and challenges. This study investigates a swarm-based approach for debris removal missions. A mother spacecraft delivers and releases a number of small satellites, referred to as NanoTugs in this paper, in the proximity of the target debris. The swarm forms a distributed and bounded formation around the debris to support capturing operations. Before capturing, vision-based navigation is used to inspect and characterize the debris properties to identify the capturing spots. The swarm then performs de-tumbling and stabilizes the debris for de-orbiting using electric thrusters. A decentralized communication system enables coordination and task allocation among the swarm agents. This paper examines the feasibility of the proposed approach by discussing potential technologies and mission scenarios. The paper focuses on the stabilization and de-orbiting phase of a six-phase mission concept for active debris removal. The concept considers a number of 3U-sized NanoTugs randomly distributed on the surface of a large tumbling debris object. A task allocation strategy assigns control flags to each nozzle, enabling coordinated thrusting operations for the de-tumbling and de-orbiting modes. The results demonstrate successful de-tumbling and subsequent de-orbiting of the debris to a lower Earth orbit altitude. For the de-tumbling mode, a Lyapunov-based control law is used to derive the unsaturated torque input for attitude control, which is then adjusted to account for nozzle actuation limits. In the de-orbiting phase, thrust is applied in directions with the highest anti-velocity projection, following Gauss' variational equations to maximize the change in the semi-major axis. The findings provide a foundation for future studies to investigate the trade-offs between the number of NanoTugs, de-orbiting time, and propellant consumption, as well as to extend the analysis to other mission phases.