Guidance Strategy for Autonomous Inspection of Unknown Non-Cooperative Resident Space Objects
Michele Maestrini, Pierluigi Di Lizia
Abstract
As space debris has become a cause of concern for space operations around Earth, active debris removal and satellite servicing missions have gained increasing attention. Within this framework, in specific scenarios, the chaser might be asked to operate autonomously in the vicinity of a non-cooperative, unknown target. This paper presents a sampling-based receding-horizon motion planning algorithm that selects inspection maneuvers while taking many complex constraints into account. The proposed guidance solution is compared with classical approaches and it is shown to take advantage of the characteristics of the natural dynamics of the relative motion to outperform them. In addition, the impact of different input sampling exploration strategies is explored to propose a simple and more robust approach based on subset simulation.