Several communication models in multiple unmanned aerial vehicles

In this paper we examine solutions for connecting UAVs, proposing solutions for adhering ad-hoc UAVs, and proposing communication models among UAVs, UAVs suggesting methods group formation.

Công nghệ thông tin SEVERAL COMMUNICATION MODELS IN MULTIPLE UNMANNED AERIAL VEHICLES Đồn Văn Hòa1*, Hoa Tất Thắng2 Abstract: The role of UAV is increasingly important in today's society In the military, the UAV performs reconnaissance missions In civilian life, UAVs carry out observation, search and rescue or transport of goods to remote, rugged areas Up until now, the UAVs are largely controlled by a single underground control station This model reveals weaknesses for multiple UAV systems by overburdening ground stations In this paper we examine solutions for connecting UAVs, proposing solutions for adhering ad-hoc UAVs, and proposing communication models among UAVs, UAVs suggesting methods group formation Keywords: UAVs; Communication models; Air-Ground Communications; Multipoint-to-Point UAV Communications with IEEE 802.11 INTRODUCTION UAVs present some of the most difficult design challenges It is because of the need to package a high level of computing power and data collection/distribution components within minimal size, weight, and power (SWaP) constraints-all while preserving ruggedized capabilities to operate in very demanding environments UAV engineers must also ascribe a high priority to security Secure communication links are vital for UAV operation, both to control the UAV based on mission objectives and to deliver data reliably to mission controllers on the ground Encryption and decryption are inherent requirements, adding complexity and cost in the UAV electronics Advanced UAV sensor payloads are acquiring a wealth of data, including fullmotion video (FMV) and high-definition (HD) images Bandwidth is often limited, however, and can prevent the transmission, sharing, and display of mission-critical information Such network limitations are driving the need for efficient data processing directly on the UAV The ability to as much autonomous onboard processing as possible and to reduce the volume of data exchanged between the UAV and ground station The goal is to exchange processed information instead of a raw data stream [2] The key to the future of drones will be their ability to work together Managing multiple drones is a unique challenge, given that each UAV type has proprietary control systems Until now, it is still a difficult problem to tie UAVs together One of the most significant tests of autonomous systems under development by the Department of Defense, the Strategic Capabilities Office, partnering with Naval Air Systems Command, successfully demonstrated one of the world’s largest micro-drone swarms at China Lake, California The test, conducted in October 2016 and documented on Sunday’s CBS News program “60 Minutes”, consisted of 103 Perdix drones launched from three F/A-18 Super Hornets [1] The micro- 220 Đ V Hòa, H T Thắng, “Several communication models … unmanned aerial vehicles.” Thông tin khoa học công nghệ drones demonstrated advanced swarm behaviors such as collective decisionmaking, adaptive formation flying, and self-healing UAVs in these cases are not individually programmed to perform synchronous tasks, but rather as a collective unit that shares a distributed processing system to make decisions No UAV is the leader, they are compatible with each other like birds in nature SYSTEM ARCHITECTURE A multi UAV system can operate in centralized and decentralized mod In the centralized system, an underground object (system) collects information from UAVs, makes decisions for them and update mission or tasks In the decentralized system, UAVs collaborate in different levels to achieve system goal and exchange information to share tasks and make collective decision The multi UAV system need to: Observe the environment; valuate their own observations and information received from other UAVs and reason them; act in effective manner Ordinarily, communications between air ambulance, police air support, SAR helicopter, and land SAR teams usually are via the ground to air channel as identified in the National Band Plan wd inertial measurement unit (IMU) module that provides the position and orientation The quadrocopter flies in the air and communicates via IEEE 802.11a wireless LAN to an access point (AP) at the ground The wireless cards are configured to use the 802.11a channel 48 (5.240 GHz) A computer at the ground is used to control the measurements; it is connected via Ethernet to the AP The AP consists of Ubiquiti’s RouterStation and Ubiquiti SR71- A 802.11abgn mini-PCI module The AP is put on a tripod and elevated to a height of approximately m The 802.11abgn mini-PCIe module from Spark LAN WPEA- 127N is used on the UAV The experiment showed that, even at the farthest range (