Autonomous unmanned aerial vehicles in search and rescue missions using real-time cooperative model predictive control
| Autor: | Rune Storvold, Diego B. Haddad, Tor Arne Johansen, Luciano Netto de Lima, Christopher Dahlin Rodin, Fabio Augusto de Alcantara Andrade, Carlos Alberto Moraes Correia, Anthony Reinier Hovenburg |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Coordinated flight
0209 industrial biotechnology Computer science model predictive control UAV Real-time computing 020101 civil engineering JSBSim ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Kinematics lcsh:Chemical technology Biochemistry Article 0201 civil engineering Analytical Chemistry 020901 industrial engineering & automation Flight dynamics lcsh:TP1-1185 Motion planning Electrical and Electronic Engineering Instrumentation path planning Search and rescue particle swarm optimization DUNE Ardupilot Particle swarm optimization Atomic and Molecular Physics and Optics search and rescue Model predictive control software in the loop unmanned aerial vehicles |
| Zdroj: | Sensors, Vol 19, Iss 19, p 4067 (2019) Sensors Volume 19 Issue 19 Sensors (Basel, Switzerland) 19:4067 |
| Popis: | Unmanned Aerial Vehicles (UAVs) have recently been used in a wide variety of applications due to their versatility, reduced cost, rapid deployment, among other advantages. Search and Rescue (SAR) is one of the most prominent areas for the employment of UAVs in place of a manned mission, especially because of its limitations on the costs, human resources, and mental and perception of the human operators. In this work, a real-time path-planning solution using multiple cooperative UAVs for SAR missions is proposed. The technique of Particle Swarm Optimization is used to solve a Model Predictive Control (MPC) problem that aims to perform search in a given area of interest, following the directive of international standards of SAR. A coordinated turn kinematic model for level flight in the presence of wind is included in the MPC. The solution is fully implemented to be embedded in the UAV on-board computer with DUNE, an on-board navigation software. The performance is evaluated using Ardupilot&rsquo s Software-In-The-Loop with JSBSim flight dynamics model simulations. Results show that, when employing three UAVs, the group reaches 50% Probability of Success 2.35 times faster than when a single UAV is employed. |
| Databáze: | OpenAIRE |
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