378 research outputs found
3D Real-Time Energy Efficient Path Planning for a Fleet of Fixed-Wing UAVs
No full textUAV 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
Quadrotor UAV 3D Path Planning with Optical-Flow-based Obstacle Avoidance
No full textA 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
The 30th Mediterranean Conference on Control and Automation [Conference Reports]
No full textPresents information on the above named conference
UAV Model-based Flight Control with Artificial Neural Networks: A Survey
No full textModel-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
Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers
No full textThe following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera
A Survey of Artificial Neural Networks with Model-based Control Techniques for Flight Control of Unmanned Aerial Vehicles
No full textMars Sample Return Mission: Mars Ascent Vehicle Propulsion Design
No full textThe aim of this research is to analyze a potential Mars Sample Return (MSR) mission through the study of an optimized design of the Mars Ascent Vehicle (MAV) propulsion system. The main goal of the MSR mission is to return to Earth samples of rocks and dust collected by a rover operating on the surface of Mars, and conveyed to the MAV into an Orbit Sample (OS) canister. The MAV must accomplish an initial ascent phase from the Mars surface to a circular Low Mars Orbit (LMO) with a radius of 500 Km and 30° inclination, and then with its second stage it must circularize into the target LMO where it releases the OS payload. A combination of the MAV and a second vehicle, the Mars Earth Return Vehicle (MERV) orbiter, is required to fulfill the final return phase from Mars to the Earth. After completing three different phases of rendezvous operations, with a final Hohmann Transfer the MERV is able to bring the OS to Earth with its payload. A spreadsheet model enables the evaluation of two different MAV architecture: a two-stage solid rocket, and a two-stage hybrid rocket. The study is based on the main rocket science equations, including the Tsiolkovsky Rocket Equation that calculates the change in velocity Delta V for the two stages of the MAV and the amount of propellant needed for both stages. From the analysis it can be noted that the two-stage hybrid design has significant advantages, firstly in terms of Gross Lift Off Mass GLOM (270 Kg) when compared to the solid solution (355 Kg). The hybrid rocket also has lower mass by up to 60 Kg since it does not require a thermal igloo. Finally, the mass fractions for both stages are comparable, and the required Delta V for the hybrid stages are less than those needed for the solid, allowing considerable fuel savings. The hybrid solution is ultimately preferred, considering the best performance related to the thermal fuel properties enabling the MAV to safely operated in the harsh Martian environment
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