999 research outputs found

    3D Real-Time Energy Efficient Path Planning for a Fleet of Fixed-Wing UAVs

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    UAV path planning requires finding an optimal (or sub-optimal) collision free path in a cluttered environment, while taking into account geometric, physical and temporal constraints, eventually allowing UAVs to perform their tasks despite several uncertainty sources. This paper reviews the current state-of-the-art in path planning, and subsequently introduces a novel node-based algorithm based on the called EEA*. EEA* is based on the A* Search algorithm and aims at mitigating some of its key limitations. The proposed EEA* deals with 3D environments, it provides robustness quickly converging to the solution, it is energy efficient and it is realtime implementable and executable. Along with the proposed EEA*, a local path planner is developed to cope with unknown dynamic threats in the environment. Applicability and effectiveness is first demonstrated via simulated experiments using a fixed-wing UAV that operates in different mountain-like 3D environments in the presence of several unknown dynamic obstacles. Then, the algorithm is applied in a multi-agent setting with three UAVs that are commanded to follow their respective paths in a safe way. The energy efficiency of the EEA* algorithm has also been tested and compared with the conventional A* algorithm

    Panos Valavanis, Hysplex. The Starting Mechanism in Ancient Stadia. A Contribution to Ancient Greek Technology

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    Vanhove Doris. Panos Valavanis, Hysplex. The Starting Mechanism in Ancient Stadia. A Contribution to Ancient Greek Technology. In: L'antiquité classique, Tome 70, 2001. pp. 402-403

    Panos Valavanis, Hysplex. The Starting Mechanism in Ancient Stadia. A Contribution to Ancient Greek Technology

    No full text
    Vanhove Doris. Panos Valavanis, Hysplex. The Starting Mechanism in Ancient Stadia. A Contribution to Ancient Greek Technology. In: L'antiquité classique, Tome 70, 2001. pp. 402-403

    Quadrotor UAV 3D Path Planning with Optical-Flow-based Obstacle Avoidance

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    A real-time waypoint-based 3D local path planning algorithm is proposed for obstacle avoidance using the optical flow obtained by a frontal monocular camera mounted on a quadrotor UAV. The algorithm accounts for vertical and horizontal obstacle avoidance, as well as for avoidance of frontally approaching obstacles. Implementation and testing are carried out in the ROS environment and the algorithm effectiveness is demonstrated via Gazebo simulations. Realtime algorithm performance is also assessed through software profiling and in terms of worst case execution time using the NVIDIA Jetson TX1 and RaspberryPi 4 for hardware-in-the-loop (HIL) tests

    UAV Model-based Flight Control with Artificial Neural Networks: A Survey

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    Model-Based Control (MBC) techniques have dominated flight controller designs for Unmanned Aerial Vehicles (UAVs). Despite their success, MBC-based designs rely heavily on the accuracy of the mathematical model of the real plant and they suffer from the explosion of complexity problem. These two challenges may be mitigated by Artificial Neural Networks (ANNs) that have been widely studied due to their unique features and advantages in system identification and controller design. Viewed from this perspective, this survey provides a comprehensive literature review on combined MBC-ANN techniques that are suitable for UAV flight control, i.e., low-level control. The objective is to pave the way and establish a foundation for efficient controller designs with performance guarantees. A reference template is used throughout the survey as a common basis for comparative studies to fairly determine capabilities and limitations of existing research. The end-result offers supported information for advantages, disadvantages and applicability of a family of relevant controllers to UAV prototypes

    Vascular disorders of the Spine and Spinal Cord

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