Use of Variable Incidence Angle for Glide Slope Control of Autonomous Parafoils

Slegers, Nathan; Beyer, Eric; Costello, Mark

doi:10.2514/1.32099

Cited by 83 publications

(44 citation statements)

References 15 publications

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“…Recent efforts by Ward and Costello [14,29] have also demonstrated the potential for improved glide-slope tracking through both online system identification, and by exploiting the longitudinal control coupling between incidence angle and symmetric brake deflection. To summarize, while the above approaches [14,[27][28][29] take some measures to account for the effect of wind uncertainty on the parafoil landing position, they offer no robustness to interaction with terrain obstacles, and are subject to the fundamental constraining of the solution space imposed by the glide-slope approach paradigm.…”

Section: Literature Reviewmentioning

confidence: 99%

Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

Ellertson

2016

AIAA Infotech @ Aerospace

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Autonomously guided parafoil systems can deliver supplies and aid to remote, geographically diverse locations, while providing important safety and logistical advantages over ground-based transportation methods. A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into difficult, complex terrain. Parafoil guidance algorithms must be able to generate feasible trajectory solutions to the target location within highly constrained terrain environments and from a wide range of initial conditions. Robustness is critical for successful payload delivery in the presence of uncertain atmospheric wind disturbances.This thesis presents two online trajectory planning algorithms for autonomous parafoil guidance in complex terrain and wind environments. These -algorithms are capable of operating from arbitrary initial conditions, including altitude, and are robust to wind disturbances that may be highly dynamic throughout terminal descent. The first algorithm, known as Analytic CC-RRT, builds upon the framework of chance-constrained rapidly-exploring random trees (CC-RRT). This planner enables fast incremental trajectory construction in cluttered, non-convex environments, while using chance constraints to ensure probabilistic feasibility. The designed costto-go function prioritizes target accuracy and upwind landings through the selection of partial paths that intelligently consider current and reachable future states. A trained multi-class wind uncertainty model is introduced to classify and anticipate the effect of future wind disturbances online. Utilizing this model, robustness to wind variations is achieved via a novel analytic uncertainty sampling technique, allowing the probability of constraint violation to be efficiently evaluated against arbitrary and aggressive terrain.The second algorithm, known as CC-BLG, incorporates the Analytic CC-RRT proactive wind model and uncertainty sampling technique into the optimized BandLimited Guidance (BLG) framework. Through the design of a novel risk-based objective function, CC-BLG trajectories efficiently balance the parafoil performance metrics of landing accuracy and landing speed with the risk of off-nominal terrain 3 collisions caused by future wind disturbances. Proposed extensions to the analytic uncertainty sampling technique are shown to yield enhanced planning robustness by refining the estimation of trajectory risk. Multi-phase CC-BLG path planning enables initialization of parafoil terminal guidance from potentially high altitudes, while discrete reachability set approximation is used to maintain robust obstacle avoidance over disjoint planning horizons.Extensive Monte Carlo simulation analysis demonstrates that the Analytic CC-RRT and CC-BLG algorithms achieve significant improvements in mean and worstcase landing accuracy within complex terrain scenarios relative to the state-of-the-art Band-Limited Guidance (BLG) algorithm. Flight test experiments conducted with a full-scal...

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Section: Literature Reviewmentioning

confidence: 99%

Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

Ellertson

2016

AIAA Infotech @ Aerospace

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“…This makes the approach sensitive to uncertainty in both the vehicle dynamics and environment, especially given that the glide-slope surface shifts as a function of current wind conditions. Slegers et al 9 track the glide-slope using nonlinear model predictive control (MPC), improving rejection of small-scale disturbances, but still require long-term glide-slope tracking. Bergeron et al 10 use feedback control, known as glideslope guidance (GSG), to drive the goal approach based on the estimated glide-slope and wind conditions.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Other approaches in the literature require an upper limit on the initial altitude for terminal guidance to remain computationally tractable 6,[8][9][10]12,13 . Figure 11 and Table 6 present simulation results on the valley terrain when the initial Figure 11.…”

Section: Viiid Cc-rrt Invariance To Initial Altitudementioning

confidence: 99%

Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty

Luders

Sugel

How

2013

AIAA Infotech@Aerospace (I@A) Conference

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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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“…Slegers et al [2] track the glide-slope using nonlinear model predictive control (MPC), improving rejection of small-scale disturbances, but also require long-term glide-slope tracking. Bergeron et al [3] use feedback control, known as glide-slope guidance (GSG), to drive the approach to the goal based on the estimated glide-slope and wind conditions.…”

Section: Introductionmentioning

confidence: 99%

Wind Uncertainty Modeling and Robust Trajectory Planning for Autonomous Parafoils

Luders

Ellertson

How

et al. 2016

Journal of Guidance, Control, and Dynamics

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A key challenge facing modern airborne delivery systems, such as parafoils, is the ability to accurately and consistently deliver supplies into dicult, complex terrain. Robustness is a primary concern, given that environmental wind disturbances are often highly uncertain and time-varying. This paper presents a new on-line trajectory planning algorithm that enables a large, autonomous parafoil with under-actuated dynamics to robustly execute collision avoidance and precision landing on mapped terrain, even with signicant 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 modeling and classication is used to anticipate future disturbances, while a novel uncertainty-sampling technique ensures that robustness to future variation is eciently maintained. The designed cost-to-go function enables selection of partial paths which intelligently trade o 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.

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Use of Variable Incidence Angle for Glide Slope Control of Autonomous Parafoils

Cited by 83 publications

References 15 publications

Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

Analytic Chance Constraints for the Robust Guidance of Autonomous Parafoils

Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty

Wind Uncertainty Modeling and Robust Trajectory Planning for Autonomous Parafoils

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