Abstract
This paper addresses the control of a fleet of unmanned aerial systems (UAVs), termed as drones, for flight formation problems. Getting drones to fly in formation is a relevant problem to be solved when cooperative cargo transportation is desired. A general approach for this problem considers the coordination of a fleet of UAVs, by fusing all information coming from several individual sensors posed on each UAVs. However, this approach induces a high cost as every UAV should have its advanced perception system. As an alternative, this paper proposes the use of a single perception system by a fleet composed of several elementary drones (workers) with primitive low-cost sensors and a leader drone carrying a 3D perception source. We propose a Quadral-Fuzzy approach to ensure that all drones fly in formation and will not collide with each other or with environment obstacles. We also develop a new way to compute potential fields based on possibility fuzzy (fuzziness) measure with the focus of avoiding collisions between the drones. The proposed approach encompasses four high-coupled intelligent controllers that respectively control the leader and worker drones’ motion and implement obstacle and collision avoidance procedures. Simulation results using a fleet of four aerial drones are presented, showing the potential for solving usual problems to flights in formation, such as dodging obstacles, avoiding collisions between the drones, among others.
Highlights
Nowadays, unmanned aerial vehicles (UAVs) are used in several applications from military and civilian domains such as forest fire monitoring, surveillance, terrain mapping, and surveying, tracking, disaster management, blood or medical equipment delivery, and others [1]–[5]
This paper addresses the control of a fleet of unmanned aerial systems (UAVs), termed as drones, for flight formation problems
A general approach for this problem considers the coordination of a fleet of UAVs, by fusing all information coming from several individual sensors posed on each UAVs. This approach induces a high cost as every UAV should have its advanced perception system
Summary
Nowadays, unmanned aerial vehicles (UAVs) are used in several applications from military and civilian domains such as forest fire monitoring, surveillance, terrain mapping, and surveying, tracking, disaster management, blood or medical equipment delivery, and others [1]–[5]. Flexible, lightweight, low-cost, and easy to use UAV with the potential to reduce the cost and time in the logistic field. An extensive survey of aerial drones for civilian applications is given in [6]. From this survey, one of the most. The associate editor coordinating the review of this manuscript and approving it for publication was Yongping Pan. promising applications of aerial drones is for autonomous cargo transport and delivery by e-commerce retailers and for express delivery of perishable goods such as food or medicines. The sensor fusion with accurate high location sensors, such as Real Time Kinematic GPS [9], allows to obtain the drone position in a global reference system; (3) Avoid obstacles and collisions: it is necessary to establish a flyable collision-free path in a
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