Mathematical modeling for flocking flight of autonomous multi-UAV system, including environmental factors

Abstract

In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

Design of Smart City Considering Carbon Emissions under The Background of Industry 5.0

“…The Internet of Things (IoT) technology [22]- [23], drones [24]- [25], and high-precision sensors [26] provide the hardware foundation for smart patrol systems. Before conducting patrols, the offline trajectory planner needs to first plan a global trajectory for the drone based on its patrol range, three-dimensional environment, and relevant parameters [27]. A large number of existing robot trajectory planning schemes [28]- [29] and heuristic algorithms [30]- [31] have provided possibilities for the establishment of drone-based patrol systems in smart cities.…”

“…Minimizing carbon emissions and minimizing noise pollution meet the environmental and people-oriented requirements of Industry 5.0. Before conducting urban patrol tasks with drones, it is necessary to first plan a feasible flight path for the drones [27]. The purpose of the unmanned aerial vehicle (UAV) based patrol system designed in this study is to complete patrol tasks in smart cities with minimal energy consumption while protecting public privacy, providing technical support for emergency response and post disaster recovery in smart cities.…”

The Identification of Emerging Technologies of Automotive Semiconductor

“…The technology advances further as for data processing speed and reliability. The role of automotive semiconductor technology has expanded to implement innovative technologies of next-generation transportation means such as autonomous shuttles and flying cars [18][19][20].…”

Consensus-based clustering and data aggregation in decentralized network of multi-agent systems

“…In addition to several advantages, decentralized control systems have one main challenge: communication between agents to perform coordination ( Kwon & Hwang, 2020 ). Consensus ( Choi, Brunet & How, 2009 ) may be one of the solutions to this.…”