Thomas Stastny

Long-Endurance Sensing and Mapping Using a Hand-Launchable Solar-Powered UAV

This paper investigates and demonstrates the potential for very long endurance autonomous aerial sensing and mapping applications with AtlantikSolar, a small-sized, hand-launchable, solar-powered fixed-wing unmanned aerial vehicle. The platform design as well as the on-board state estimation, control and path-planning algorithms are overviewed. A versatile sensor payload integrating a multi-camera sensing system, extended on-board processing and high-bandwidth communication with the ground is developed. Extensive field experiments are provided including publicly demonstrated field-trials for search-and-rescue applications and long-term mapping applications. An endurance analysis shows that AtlantikSolar can provide full-daylight operation and a minimum flight endurance of 8 h throughout the whole year with its full multi-camera mapping payload. An open dataset with both raw and processed data is released and accompanies this paper contribution.

Model Predictive Control for Trajectory Tracking of Unmanned Aerial Vehicles Using Robot Operating System

In this chapter, strategies for Model Predictive Control (MPC) design and implementation for Unmaned Aerial Vehicles (UAVs) are discussed. This chapter is divided into two main sections. In the first section, modelling, controller design and implementation of MPC for multi-rotor systems is presented. In the second section, we show modelling and controller design techniques for fixed-wing UAVs. System identification techniques are used to derive an estimate of the system model, while state of the art solvers are employed to solve the optimization problem online. By the end of this chapter, the reader should be able to implement an MPC to achieve trajectory tracking for both multi-rotor systems and fixed-wing UAVs.

A Collaborative Framework for 3D Mapping Using Unmanned Aerial Vehicles

This paper describes an overview of a generic framework for collaboration among humans and multiple heterogeneous robotic systems based on the use of a formal characterization of delegation as a speech act. The system used contains a complex set of integrated software modules that include delegation managers for each platform, a task specification language for characterizing distributed tasks, a task planner, a multi-agent scan trajectory generation and region partitioning module, and a system infrastructure used to distributively instantiate any number of robotic systems and user interfaces in a collaborative team. The application focusses on 3D reconstruction in alpine environments intended to be used by alpine rescue teams. Two complex UAV systems used in the experiments are described. A fully autonomous collaborative mission executed in the Italian Alps using the framework is also described.

Robotic technologies for solar-powered UAVs: Fully autonomous updraft-aware aerial sensing for multiday search-and-rescue missions

Large-scale aerial sensing missions can greatly benefit from the perpetual endurance capability provided by high-performance low-altitude solar-powered UAVs. However, today these UAVs suffer from small payload capacity, low energetic margins and high operational complexity. To tackle these problems, this paper presents four individual technical contributions and integrates them into an existing solar-powered UAV system: First, a lightweight and power-efficient day/night-capable sensing system is discussed. Second, means to optimize the UAV platform to the specific payload and to thereby achieve sufficient energetic margins for day/night-flight with payload are presented. Third, existing autonomous launch and landing functionality is extended for solar-powered UAVs. Fourth, as a main contribution an extended Kalman filter-based autonomous thermal updraft tracking framework is developed. Its novelty is that it allows the end-to-end integration of the thermal-induced roll moment into the estimation process. It is assessed against unscented Kalman filter and particle filter methods in simulation and implemented on the aircraft’s low-power autopilot. The complete system is verified during a 26-hour search-and-rescue aerial sensing mockup mission that represents the first-ever fully-autonomous perpetual endurance flight of a small solar-powered UAV with a day/night-capable sensing payload. It also represents the first time that solar-electric propulsion and autonomous thermal updraft tracking are combined in flight. In contrast to previous work that has focused on the energetic feasibility of perpetual flight, the individual technical contributions of this paper are considered core functionality to guarantee ease-of-use, effectivity and reliability in future multi-day aerial sensing operations with small solar-powered UAVs.

Victim Detection from a Fixed-Wing UAV: Experimental Results

This paper outlines a method to identify humans from a low-altitude fixed-wing UAV relying on various visual and inertial sensors including an infrared camera. The work draws inspiration from the need to detect victims in disaster scenarios in real-time, providing needed aid to rescue efforts. Such work can also be easily employed for surveillance related applications. We start by pointing out various challenges from camera imperfections, viewpoint, altitude, and synchronization. We provide a pipeline to efficiently fuse thermal and visual aerial imagery for robust real-time detections. Confident detections are tracked across various frames and the real-time GPS locations of the victims are conveyed. Performance of our detection algorithm is evaluated in a real-world victim detection scenario from an autonomous fixed-wing aircaft.

Model-based wind estimation for a hovering VTOL tailsitter UAV

To many unmanned aerial vehicle (UAV) designs, the lack of information about the wind speed and direction is a limiting factor in achieving robust outdoor flight. This paper addresses the problem of wind estimation onboard a hovering vertical take-off and landing (VTOL) tailsitter UAV. The proposed estimation framework makes use of the standard onboard sensor suite: inertial measurement unit (IMU), global positioning system (GPS) and a magnetometer. No additional airspeed sensor is needed. As a result, the autopilot is provided with an estimate of the wind velocity vector in the horizontal (north-east) plane. An aerodynamic model of the vehicle has been derived and used in a Kalman filter framework to estimate the horizontal wind velocity vector in real-time. The wind estimator has been implemented onboard the UAVs autopilot and validated in real flight. As a result, we successfully obtain the direction and speed of the wind with an estimation accuracy close to the accuracy range of the ground truth measurement. Furthermore, the derived grey-box model allows to generalise the framework to different airframes.

Collaborative 3D Reconstruction Using Heterogeneous UAVs: System and Experiments

This paper demonstrates how a heterogeneous fleet of unmanned aerial vehicles (UAVs) can support human operators in search and rescue (SaR) scenarios. We describe a fully autonomous delegation framework that interprets the top-level commands of the rescue team and converts them into actions of the UAVs. In particular, the UAVs are requested to autonomously scan a search area and to provide the operator with a consistent georeferenced 3D reconstruction of the environment to increase the environmental awareness and to support critical decision-making. The mission is executed based on the individual platform and sensor capabilities of rotary- and fixed-wing UAVs (RW-UAV and FW-UAV respectively): With the aid of an optical camera, the FW-UAV can generate a sparse point-cloud of a large area in a short amount of time. A LiDAR mounted on the autonomous helicopter is used to refine the visual point-cloud by generating denser point-clouds of specific areas of interest. In this context, we evaluate the performance of point-cloud registration methods to align two maps that were obtained by different sensors. In our validation, we compare classical point-cloud alignment methods to a novel probabilistic data association approach that specifically takes the individual point-cloud densities into consideration.

Model-based transition optimization for a VTOL tailsitter

This paper addresses the problem of trajectory optimization for the transition of a Vertical Take-off and Landing (VTOL) tailsitter Unmanned Aerial Vehicle (UAV). The proposed strategy performs a model based optimization, where the model represents the closed-loop dynamics of the UAV with low-level control, ensuring attitude stabilization over the whole trajectory. We discuss the design of an optimization framework, vehicle modeling, and elaborate on the cost function construction. An additional feedback gain is implemented on the throttle channel with altitude discrepancies as its input to provide some level of robustness to wind disturbances. The overall approach is verified in simulation and experimental results with a focus on optimization of the back-transition (cruise-to-hover) of the Wingtra S100 VTOL tailsitter.

Gone with the wind: Nonlinear guidance for small fixed-wing aircraft in arbitrarily strong windfields

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this paper we present a principled nonlinear guidance strategy, addressing this problem. More broadly, we propose a methodology for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.