Unmanned Aerial Vehicles (UAVs) play an ever increasing role in a wide variety of scenarios in both the civilian and military sector, carrying out tasks like traffic surveillance, firefighting, or reconnaissance missions. Furthermore, the use of groups of vehicles, or swarms, has been shown to accomplish certain objectives more efficiently and more effectively than a single vehicle can, for example in terrain mapping or search missions. In all these scenarios, the autonomous vehicles need to fly on trajectories that match their flight envelope, are as short as possible, and most importantly, avoid collisions with obstacles and other UAVs at all cost. In order to achieve this, MILP (Mixed-Integer Linear Programming) is used as the optimization principle. MILP extends regular linear programming to include variables that are constrained to integer or binary values. Thus, MILP offers the possibility to add logical and decision making constraints into the optimization, such as obstacle and collision avoidance. However, finding long-range minimum-time trajectories in environments with many obstacles is a complex optimization problem. In this paper, a Model Predictive Control (MPC) approach is chosen to decrease computational complexity and limit computation time, therefore making the algorithm capable of real-time calculations as well as handling unknown or dynamically changing environments. The presented algorithm is capable of calculating near-optimal flight trajectories to ensure that the UAV swarm carries out its mission in the minimum time.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Mission-Based UAV Swarms: Base Defense

    C. G. Escamilla | NTIS | 2020


    Collaborative Mission Planning & Autonomous Control Technology (CoMPACT) System Employing Swarms of UAVs

    Boskovic, J. / Knoebel, N. / Moshtagh, N. et al. | British Library Conference Proceedings | 2009


    Collaborative Mission Planning & Autonomous Control Technology (CoMPACT) System Employing Swarms of UAVs

    Boskovic, Jovan / Knoebel, Nathan / Moshtagh, Nima et al. | AIAA | 2009



    The Adaptability of Countermeasures Against UAV Swarms in Typical Mission Scenarios

    Yan, Jia’ding / Xie, Hai’bin / Zhuang, Dong’ye | Springer Verlag | 2022