Thermal Centering Control for Autonomous Soaring; Stability Analysis and Flight Test Results

The article of record as published may be found at https://doi.org/10.2514/1.51691This paper addresses the challenge of using autonomous soaring gliders to search for and exploit thermal lift to extend the gliders’ endurance. For this purpose, a simple thermal centering controller is proposed. The paper includes theoretical analysis of stability and convergence properties of this controller. Using an exponential Gaussian function to represent the updraft field of a thermal, the Lyapunov type analysis shows the proposed controller to be asymptotically stable and determines its region of attraction. The size of the region of attraction is shown to be a function of the feedback gain that can be adjusted for any given strength and geometry of thermal. The paper additionally presents simulation and flight test results that verify the performance of the proposed controller. The results of the flight trials also confirm the feasibility and effectiveness of using autonomous thermal soaring to extend endurance for unmanned gliders

Time-Critical Cooperative Path Following of Multiple UAVs: Case Studies

This paper describes a multi-vehicle motion control framework for time-critical cooperative missions and evaluates its performance by considering two case stud- ies: a simultaneous arrival mission scenario and a sequential auto-landing of a fleet of UAVs. In the adopted setup, the UAVs are assigned nominal spatial paths and speed profiles along those, and the vehicles are then tasked to execute co- operative path following, rather than “open-loop” trajectory-tracking maneuvers. This cooperative strategy yields robust behavior against external disturbances by allowing the UAVs to negotiate their speeds along the paths in response to coordi- nation information exchanged over the supporting communications network. The approach applies to teams of heterogeneous vehicles and does not necessarily lead to swarming behavior

Time-Critical Cooperative Path Following of Multiple UAVs over Time-Varying Networks

submitted to AIAA Journal of Guidance, Control and Dynamic

Optimal Motion Planning for Localization of Avalanche Victims by Multiple UAVs

This letter proposes a method for localization of avalanche victims by multiple UAVs. The method consists of three main parts. First, assuming that the UAVs and the victim are equipped with ARTVA receivers and a transmitter, respectively, we introduce a mathematical model of the receiver, which is used to estimate the position of the victim. Second, we derive a closed-form expression indicating the performance of this estimator. In particular, we show that the victim's observability index is captured by the persistency of excitation of a function of the UAVs trajectories. Third, we design and implement a motion planning algorithm that uses the estimation and the estimator's performance function for the (near) real-time generation of trajectories that guarantee feasible, safe, and time-efficient localization of avalanche victims

Optimal Motion Planning for Differentially Flat Systems Using Bernstein Approximation

The article of record as published may be found at https://doi.org/10.1109/LCSYS.2017.2778313This letter presents a computational frame- work to efficiently generate feasible and optimal trajec- tories for differentially flat autonomous vehicle systems. We formulate the optimal motion planning problem as a continuous-time optimal control problem, and approx- imate it by a discrete-time formulation using Bernstein polynomials. These polynomials allow for efficient com- putation of various constraints along the entire trajectory, and are particularly convenient for generating trajectories for safe operation of multiple vehicles in complex envi- ronments. The advantages of the proposed method are investigated through theoretical analysis and numerical examples

Optimal Motion Planning for Differentially Flat Systems Using Bernstein Approximation

The article of record as published may be found at https://doi.org/10.1109/LCSYS.2017.2778313This letter presents a computational frame- work to efficiently generate feasible and optimal trajec- tories for differentially flat autonomous vehicle systems. We formulate the optimal motion planning problem as a continuous-time optimal control problem, and approx- imate it by a discrete-time formulation using Bernstein polynomials. These polynomials allow for efficient com- putation of various constraints along the entire trajectory, and are particularly convenient for generating trajectories for safe operation of multiple vehicles in complex envi- ronments. The advantages of the proposed method are investigated through theoretical analysis and numerical examples

Noh performance of Yuya, Hōshō Fusao, Mar 1969

This article focuses on the problem of computing a control law for a particular class of tail-sitter aircraft able to switch their flight configuration from hover to level flight and vice-versa. We address the problem of steering a Ducted Fan UAV along a given path (path following problem) so as to meet spatial constraints. One possible scenario is where a vehicle is required to execute collision-free maneuvers under strict spatial constraints and arrive at final destination while pointing with a camera to a moving target. Path following control in 3D builds on a nonlinear control strategy that is first derived at the kinematic level using the Special Orthonormal Group (SO(3)) theory. The research activity presented in the paper is partially framed within the European project AIRobots

Time-Critical Cooperative Path Following of Multiple Unmanned Aerial Vehicles over Time-Varying Networks

The article of record as published may be found at https://doi.org/10.2514/1.56538This paper addresses the problem of steering a fleet of unmanned aerial vehicles along desired three-dimensional paths while meeting stringent spatial and temporal constraints. A representative example is the challenging mission scenario where the unmanned aerial vehicles are tasked to cooperatively execute collision-free maneuvers and arrive at their final destinations at the same time. In the proposed framework, the unmanned aerial vehicles are assigned nominal spatial paths and speed profiles along those, and then the vehicles are requested to execute cooperative path following, rather than open loop trajectory tracking maneuvers. This strategy yields robust behavior against external disturbances by allowing the unmanned aerial vehicles to negotiate their speeds along the paths in response to information exchanged over the supporting communications network. The paper considers the case where the graph that captures the underlying time-varying communications topology is disconnected during some interval of time or even fails to be connected at all times. Conditions are given under which the cooperative path-following closed-loop system is stable. Flight test results of a coordinated road-search mission demonstrate the efficacy of the multi-vehicle cooperative control framework developed in the paper

Cooperative Path-Following of Multiple Multirotors over Time-Varying Networks

The article of record as published may be found at https://doi.org/10.1109/TASE.2015.2406758This paper addresses the problem of time-coordina- tion of a team of cooperating multirotor unmanned aerial vehicles that exchange information over a supporting time-varying net- work. A distributed control law is developed to ensure that the vehicles meet the desired temporal assignments of the mission, while flying along predefined collision-free paths, even in the pres- ence of faulty communication networks, temporary link losses, and switching topologies. In this paper, the coordination task is solved by reaching consensus on a suitably defined coordination state. Conditions are derived under which the coordination errors converge to a neighborhood of zero. Simulation and flight test results are presented to validate the theoretical findings

Time-Critical Cooperative Path Following of Multiple Unmanned Aerial Vehicles over Time-Varying Networks

The article of record as published may be found at https://doi.org/10.2514/1.56538This paper addresses the problem of steering a fleet of unmanned aerial vehicles along desired three-dimensional paths while meeting stringent spatial and temporal constraints. A representative example is the challenging mission scenario where the unmanned aerial vehicles are tasked to cooperatively execute collision-free maneuvers and arrive at their final destinations at the same time. In the proposed framework, the unmanned aerial vehicles are assigned nominal spatial paths and speed profiles along those, and then the vehicles are requested to execute cooperative path following, rather than open loop trajectory tracking maneuvers. This strategy yields robust behavior against external disturbances by allowing the unmanned aerial vehicles to negotiate their speeds along the paths in response to information exchanged over the supporting communications network. The paper considers the case where the graph that captures the underlying time-varying communications topology is disconnected during some interval of time or even fails to be connected at all times. Conditions are given under which the cooperative path-following closed-loop system is stable. Flight test results of a coordinated road-search mission demonstrate the efficacy of the multi-vehicle cooperative control framework developed in the paper