Robust planning for autonomous parafoil

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 112-119).Parafoil trajectory planning systems must be able to accurately guide the highly non-linear, under-actuated parafoil system from the drop zone to the pre-determined impact point. Parafoil planning systems are required to navigate highly complex terrain scenarios, particularly in the presence of an uncertain and potentially highly dynamic wind environment. This thesis develops a novel planning approach to parafoil terminal guidance. Building on the chance-constrained rapidly exploring random tree (CC-RRT) [1] algorithm, this planner, CC-RRT with Analytic Sampling, considers the non-linear dynamics, as well as the under-actuated control authority of the parafoil by construction. Additionally, CC-RRT with Analytic Sampling addresses two important limitations to state-of-the-art parafoil trajectory planners: (1) implicit or explicit constraints on starting altitude of the terminal guidance phase, and (2) a reactive or limitedly-proactive approach to handling the eect of wind uncertainty. This thesis proposes a novel formulation for the cost-to-go function, utilizing an approximation of the reachability set for the parafoil to account for the eect of vehicle heading on potential future states. This cost-to-go function allows for accurate consideration of partially planned paths, effectively removing strict constraints on starting altitude of the terminal guidance phase. The reachability set cost-to-go function demonstrates considerably improved performance over a simple LQR cost function, as well as cost-to-go functions with a glide-slope cone bias, demonstrating the eectiveness of utilizing the reachability set approximation as a means for incorporating heading dynamics. Furthermore, this thesis develops a multi-class model for characterizing the uncertain effect of wind. The wind model performs an online classication based on the observed wind measurements in order to determine the appropriate level of planner conservatism. Coupling this wind model with the method for sampling the analytic uncertainty distribution presented in this thesis, the CCRRT with Analytic Sampling planner is able to eciently account for the future eect of wind uncertainty and adjust trajectory plans accordingly, allowing the planner to operate in arbitrary terrain configurations without issue. CC-RRT with Analytic Sampling performs exceptionally well in complex terrain scenarios. Simulation results demonstrate signicant improvement on complex terrain relative to the state-of-the-art Band-Limited Guidance (BLG) [2], drastically reducing the worst case and average target miss distances. Simulation results demonstrate the CC-RRT with Analytic Sampling algorithm remains un-affected as terrain complexity increases, making it an ideal choice for applications where difficult terrain is an issue, as well as missions with targets with drastically dierent terrain conditions. Moreover, CC-RRT with Analytic Sampling is capable of starting terminal guidance at significantly higher altitudes than conventional approaches, while demonstrating no signicant change in performance.by Ian Sugel.S.M

Robust planning for autonomous parafoil

Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 112-119).Parafoil trajectory planning systems must be able to accurately guide the highly non-linear, under-actuated parafoil system from the drop zone to the pre-determined impact point. Parafoil planning systems are required to navigate highly complex terrain scenarios, particularly in the presence of an uncertain and potentially highly dynamic wind environment. This thesis develops a novel planning approach to parafoil terminal guidance. Building on the chance-constrained rapidly exploring random tree (CC-RRT) [1] algorithm, this planner, CC-RRT with Analytic Sampling, considers the non-linear dynamics, as well as the under-actuated control authority of the parafoil by construction. Additionally, CC-RRT with Analytic Sampling addresses two important limitations to state-of-the-art parafoil trajectory planners: (1) implicit or explicit constraints on starting altitude of the terminal guidance phase, and (2) a reactive or limitedly-proactive approach to handling the eect of wind uncertainty. This thesis proposes a novel formulation for the cost-to-go function, utilizing an approximation of the reachability set for the parafoil to account for the eect of vehicle heading on potential future states. This cost-to-go function allows for accurate consideration of partially planned paths, effectively removing strict constraints on starting altitude of the terminal guidance phase. The reachability set cost-to-go function demonstrates considerably improved performance over a simple LQR cost function, as well as cost-to-go functions with a glide-slope cone bias, demonstrating the eectiveness of utilizing the reachability set approximation as a means for incorporating heading dynamics. Furthermore, this thesis develops a multi-class model for characterizing the uncertain effect of wind. The wind model performs an online classication based on the observed wind measurements in order to determine the appropriate level of planner conservatism. Coupling this wind model with the method for sampling the analytic uncertainty distribution presented in this thesis, the CCRRT with Analytic Sampling planner is able to eciently account for the future eect of wind uncertainty and adjust trajectory plans accordingly, allowing the planner to operate in arbitrary terrain configurations without issue. CC-RRT with Analytic Sampling performs exceptionally well in complex terrain scenarios. Simulation results demonstrate signicant improvement on complex terrain relative to the state-of-the-art Band-Limited Guidance (BLG) [2], drastically reducing the worst case and average target miss distances. Simulation results demonstrate the CC-RRT with Analytic Sampling algorithm remains un-affected as terrain complexity increases, making it an ideal choice for applications where difficult terrain is an issue, as well as missions with targets with drastically dierent terrain conditions. Moreover, CC-RRT with Analytic Sampling is capable of starting terminal guidance at significantly higher altitudes than conventional approaches, while demonstrating no signicant change in performance.by Ian Sugel.S.M

Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty

A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into di cult, 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 signi cant 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 classi cation is used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to possible future variation is e ciently maintained. The designed cost-to-go function enables selection of partial paths which intelligently trade o 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.Charles Stark Draper Laborator

Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty

A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into di cult, 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 signi cant 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 classi cation is used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to possible future variation is e ciently maintained. The designed cost-to-go function enables selection of partial paths which intelligently trade o 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.Charles Stark Draper Laborator

Wind Uncertainty Modeling and Robust Trajectory Planning for Autonomous Parafoils

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. This paper presents a new online trajectory-planning algorithm that enables a large, autonomous parafoil with underactuated dynamics 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 that may be highly dynamic throughout terminal approach. Real-time wind uncertainty modeling and classification are used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to future wind variation is efficiently maintained. The designed cost-to-go function enables selection of partial paths that intelligently trade off between current and reachable future states, while encouraging upwind landings. Simulation results demonstrate that this algorithm reduces the worst-case impact of wind disturbances relative to state-of-the-art approaches.Charles Stark Draper Laboratory. Independent Research and Developmen