Research Area: Machine Learning
Understanding how multiple drones can coordinate and communicate is essential for advancing multi-agent robotics. Multiple drone applications are growing with technology and have reached areas such as: farming, meteorology, pollution detection, and forest fire monitoring. The focus of this paper is to illustrate how current systems manage mission control and communication strategies for multi-agent drone deployments. The primary scope was to examine papers that provide promising experimental results and analyze popular communication hardware used. Principal results included the classification of two main mission control strategies: centralized and decentralized. In addition the two most popular formation strategies leader-follower and virtual structure were compared. Finally, successful experimental frameworks that were used for practical applications were introduced and classified. Most results were limited in number of agents or were in their initial experimental stages. The literature review revealed a need for a greater focus on overall robustness of multi-agent systems.
Keywords:
Drone communications
Multi-agent UAV
Drone applications
Centralized decentralized architectures
Information exchange
Mission control
Author(s) Name: G. Pantelimon, K. Tepe, R. Carriveau & S. Ahmed
Journal name: Journal of Intelligent & Robotic Systems
Conferrence name:
Publisher name: Springer
DOI: 10.1007/s10846-018-0812-x
Volume Information: volume 95, pages 779–788 (2019)
