摘要：AbstractSampling Based Motion Planning (SBMP) techniques are widely used in robotics to plan feasible trajectories of a vehicle/robot evolving in a complex and constrained environment. Algorithms such as Rapidly Exploring Random Trees (RRT) and Sampling Based Model Predictive Optimization (SBMPO) allow for an efficient exploration of the state space, and the construction of a feasible sequence of maneuvers and trajectories that respect the kinodynamic and path constraints of the system. Proximity operations around small bodies are characterized by complex dynamics and constraints that can be easily and autonomously handled by motion planning techniques. This paper presents two motion planning algorithms designed to solve two different guidance problems: the landing on a small body and its observation. The mission scenarios considered to test the algorithms are the landing of Rosetta on the comet 67P/Churyumov-Gerasimenko and the observation of Didymain in the Didymos binary asteroid system. To conclude, the applicability of SBMP techniques to small body proximity operations are discussed. In particular, the advantages of implementing SBMP algorithms to solve complex high-level planning problems or to guide a spacecraft in a cluttered environment are highlighted.
关键词：KeywordsGuidance NavigationControl of VehiclesSpace ExplorationTransportationAutonomous SystemsTrajectoryPath PlanningMission PlanningDecision Making
