1,721,025 research outputs found

    Fixed-Wing UAV Energy Efficient 3D Path Planning in Cluttered Environments

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    UAV path planning in 3D cluttered and uncertain environments centers on finding an optimal / sub-optimal collision-free path, considering in parallel geometric, physical and temporal constraints, fox example, obstacles, infrastructure, physical or artificial landmarks, etc. This paper introduces a novel node-based algorithm, called Energy Efficient A* (EEA*), which is based on the A* search algorithm, but overcomes some of its key limitations. The EEA* deals with 3D environments, it is robust converging fast to the solution, it is energy efficient and it is real-time implementable and executable. In addition to the EEA*, a local path planner is also derived to cope with unknown dynamic threats within the working environment. The EEA* and the local path planner are first implemented and evaluated via simulated experiments using a fixed-wing UAV operating in mountain-like 3D environments, and in the presence of unknown dynamic obstacles. This is followed by evaluating a set up where three UAVs are commanded to follow their respective paths in a safe way. The energy efficiency of EEA* is also tested and compared with the conventional A* algorithm

    Sensors for missions

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    An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs).\ud \ud Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV.\ud \ud This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management

    Data fusion and tracking with multiple UAVs

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    This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications

    The safety risk management of unmanned aircraft systems

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    The safety risk management process describes the systematic application of management policies, procedures and practices to the activities of communicating, consulting, establishing the context, and identifying, analysing, evaluating, treating, monitoring and reviewing risk. This process is undertaken to provide assurances that the risks of a particular unmanned aircraft system activity have been managed to an acceptable level. The safety risk management process and its outcomes form part of the documented safety case necessary to obtain approvals for unmanned aircraft system operations. It also guides the development of an organisation’s operations manual and is a primary component of an organisation’s safety management system. The aim of this chapter is to provide existing risk practitioners with a high level introduction to some of the unique issues and challenges in the application of the safety risk management process to unmanned aircraft systems. The scope is limited to safety risks associated with the operation of unmanned aircraft in the civil airspace system and over inhabited areas. The structure of the chapter is based on the safety risk management process as defined by the international risk management standard ISO 31000:2009 and draws on aviation safety resources provided by International Civil Aviation Organization, the Federal Aviation Administration and U.S. Department of Defense. References to relevant aviation safety regulations, programs of research and fielded systems are also provided

    Correction to the Euler Lagrange multirotor model with Euler angles generalized coordinates

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    This technical note proves analytically how the exact equivalence of the Newton-Euler and Euler-Lagrange modeling formulations as applied to multirotor UAVs is achieved. This is done by deriving a correct Euler-Lagrange multirotor attitude dynamics model. A review of the published literature reveals that the commonly adopted Euler-Lagrange multirotor dynamics model is equivalent to the Newton-Euler model only when it comes to the position dynamics, but not in the attitude dynamics. Step-by-step derivations and calculations are provided to show how modeling equivalence to the Newton-Euler formulation is proven. The modeling equivalence is then verified by obtaining identical results in numerical simulation studies. Simulation results also illustrate that when using the correct model for feedback linearization, controller stability at high gains is improved

    Koopman-based Model Predictive Control of quadrotors

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    A novel formulation of model predictive control (MPC) coupled with Koopman operator theory is presented and tested for the trajectory tracking problem of a quadrotor UAV. The analytical derivation of Koopman observables allows for the quadrotor model to be written as a fully-actuated quasi-linear system which enables the control problem to be posed as a linear control problem. In fact, the adopted approach embeds the quadrotor nonlinear dynamics into a quasi-linear form through the evolution of the Koopman op-erator generalized eigenfunctions, a special kind of Koopman observables. Hence, the linear MPC formulation in Koopman coordinates is equivalent to a nonlinear implementation in the original state space. Moreover, in an enhancement from the standard feedback linearization, the Koopman based quadro-tor model does not present underactuation, which drastically simplifies the computational requirement for the solution of the MPC optimization problem. The presented methodology is tested through detailed numerical simulations and results are compared to single-loop nonlinear MPC (NMPC). The satisfactory tracking performance are additionally enhanced by the obtained computational speedup which is crucial for real time implementation of flight controllers

    Koopman operator based modeling and control of quadrotors

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    This book showcases a collection of papers that present cutting-edge studies, methods, experiments, and applications in various interdisciplinary fields. These fields encompass optimal control, guidance, navigation, game theory, stability, nonlinear dynamics, robotics, sensor fusion, machine learning, and autonomy. The chapters reveal novel studies and methods, providing fresh insights into the field of optimal guidance and control for autonomous systems. The book also covers a wide range of relevant applications, showcasing how optimal guidance and control techniques can be effectively applied in various domains, including mechanical and aerospace engineering. From robotics to sensor fusion and machine learning, the papers explore the practical implications of these techniques and methodologies

    Computer Vision Onboard UAVs for Civilian Tasks

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    Computer visión is much more than a technique to sense and recover environmental information from an UAV. It should play a main role regarding UAVs' functionality because oí the big amount oí information that can be extracted, its possible uses and applications, and its natural connection to human driven tasks, taking into account that visión is our main interface to world understanding. Our current research's focus lays on the development of techniques that allow UAVs to maneuver in spaces using visual information as their main input source. This task involves the creation of techniques that allow an UAV to maneuver towards features of interest whenever a GPS signal is not reliable or sufficient, e.g. when signal dropouts occur (which usually happens in urban áreas, when flying through terrestrial urban canyons or when operating on remote planetary bodies), or when tracking or inspecting visual targets—including moving ones—without knowing their exact UMT coordinates. This paper also investigates visual servoing control techniques that use velocity and position of suitable image features to compute the references for flight control. This paper aims to give a global view of the main aspects related to the research field of computer visión for UAVs, clustered in four main active research lines: visual servoing and control, stereo-based visual navigation, image processing algorithms for detection and tracking, and visual SLAM. Finally, the results of applying these techniques in several applications are presented and discussed: this study will encompass power line inspection, mobile target tracking, stereo distance estimation, mapping and positioning

    View Planning for Multi-View Stereo 3D Reconstruction Using an Autonomous Multicopter

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    Multi-view stereo algorithms are an attractive technique for the digital reconstruction of outdoor sites. Concerning the data acquisition process a vertical take off and landing UAV carrying a digital camera is a suitable platform in terms of mobility and flexibility in viewpoint placement. We introduce an automated UAV based data acquisition and outdoor site reconstruction system. A special focus is set on the problem of model based view planning using a coarse digital surface model (DSM) with minimal data preprocessing. The developed view planning heuristic considers a coverage, a maximum view angle and an overlapping constraint imposed by multi-view stereo reconstruction techniques. The time complexity of the algorithm is linear with respect to the size of the area of interest. We demonstrate the efficiency of the entire system in two scenarios, a building and a hillside

    An Advanced Hexacopter for Mars Exploration: Attitude Control and Autonomous Navigation

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    Mars exploration has recently witnessed major interest within the scientific community, particularly because unmanned aerial robotic platforms offer reliable alternatives for acquiring and collecting data and information from the Red Planet. However, the specific conditions of the Martian environment result in a restricted flight envelope when flying close to Mars and then landing on the surface of Mars. Therefore, in addition to the requirement to develop an aerial platform suitable for operations on Mars, autonomous navigation strategies and robust controllers are also needed for exploration tasks. It is argued that hexacopters with their relatively compact design represent a promising solution for autonomous exploration tasks on Mars, overcoming at the same time the limitations of wheel-based rovers. This research focuses on the design of a Mars Hexacopter (MHex) for a scouting mission in the Jezero region of Mars. The configuration and architecture of the hexacopter follow NASA conceptual study of the Mars Science Helicopter (MSH). Then, the mission profile for mapping Belva crater is examined, followed by a detailed approach to implement and test observer-based navigation and control strategies. A comprehensive simulated experiments environment based on the integration of ROS and Ardupilot,is also presented, used to validate the overall system architecture and mission parameters considering both the morphological shape of the explored crater and the atmospheric conditions of Mars
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