AIAA Infotech@Aerospace (I@A) Conference · 2013 · 28 citations · 25 references
EngineeringAerospace EngineeringAutonomous SystemsAerial RoboticsFlight DynamicsPath PlanningAircraft ControlAutonomous LandingManeuvering FlightMission PlanningOptimization Under UncertaintyTrajectory OptimizationAutonomous Collision AvoidanceLandingPrecision LandingReal-time Trajectory PlanningTerminal Approach TrajectoriesTrajectory PlanningTrajectory Planning For Collision AvoidanceTrajectory Planning For Landing
A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into difficult, complex terrain. Robustness is a primary concern, given that environmental wind disturbances are often highly uncertain and time-varying, coupled with under-actuated dynamics and potentially narrow drop zones. This paper presents a new on-line trajectory planning algorithm that enables a large, autonomous parafoil to robustly execute collision avoidance and precision landing on mapped terrain, even with significant wind uncertainties. This algorithm is designed to handle arbitrary initial altitudes, approach geometries, and terrain surfaces, and is robust to wind disturbances which may be highly dynamic throughout the terminal approach. Explicit, real-time wind modeling and classification is used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to possible future variation is efficiently maintained. The designed cost-to-go function enables selection of partial paths which intelligently trade off between current and reachable future states. Simulation results demonstrate that the proposed algorithm reduces the worst-case impact of wind disturbances relative to state-of-the-art approaches.
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Pattern Recognition and Machine Learning
Journal of Electronic Imaging · 2007 · 22.1K citations
Rapidly-exploring random trees : a new tool for path planning
Steven M. LaValle · 1998 · 3.6K citations