Abstract
This paper proposes a novel search method for a swarm of quadcopter drones. In the proposed method, inspired by the phenomena of swarms in nature, drones effectively look for the search target by investigating the evidence from the surroundings and communicating with each other. The position update mechanism is implemented using the particle swarm optimization algorithm as the swarm intelligence (a well-known swarm-based optimization algorithm), as well as a dynamic model for the drones to take the real-world environment into account. In addition, the mechanism is processed in real-time along with the movements of the drones. The effectiveness of the proposed method was verified through repeated test simulations, including a benchmark function optimization and air pollutant search problems. The results show that the proposed method is highly practical, accurate, and robust.
Highlights
The demand for autonomous aerial vehicles, commonly called drones, has largely increased in recent years due to their compactness and mobility, which enable them to carry out various tasks that are economically inefficient or potentially dangerous to humans
In this paper, a novel swarm search method for quadcopter drones is proposed by integrating the position update rule of the swarm intelligence algorithm and the motion controller using a dynamic model of the drones
The main contribution of this paper is that a novel drone position update mechanism for the swarm search was designed to be specific enough to consider real-time control and the real-world environment
Summary
The demand for autonomous aerial vehicles, commonly called drones, has largely increased in recent years due to their compactness and mobility, which enable them to carry out various tasks that are economically inefficient or potentially dangerous to humans. It is not easy for humans to explore rugged mountain terrains, flooded areas, or air pollution regions without drones They have been extensively employed in various search applications, such as industrial building inspections [1,2], search and rescue operations [3,4,5], and post-disaster area exploration [6,7,8]. In this paper, a novel swarm search method for quadcopter drones is proposed by integrating the position update rule of the swarm intelligence algorithm and the motion controller using a dynamic model of the drones. A swarm of more than 10 drones was employed for a search mission.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call