Abstract:
The compact flocking of relatively localized Un-manned Aerial Vehicles (UAVs) in high obstacle density areas is discussed in this paper. The presented work tackles realis...Show MoreMetadata
Abstract:
The compact flocking of relatively localized Un-manned Aerial Vehicles (UAVs) in high obstacle density areas is discussed in this paper. The presented work tackles realistic scenarios in which the environment map is not known apriori and the use of a global localization system and communication infrastructure is difficult due to the presence of obstacles. To achieve flocking in such a constrained environment, we propose a fully decentralized, bio-inspired control law that uses only onboard sensor data for safe flocking through the environment without any communication with other agents. In the proposed approach, each UAV agent uses onboard sensors to self-localize and estimate the relative position of other agents in its local reference frame. The usability and performance of the proposed approach were verified and evaluated using various experiments in a realistic robotic simulator and a natural forest. The presented experiments also validate the utility of onboard relative localization for autonomous multi-UAV applications in the absence of global localization information and communication.
Date of Conference: 30 May 2021 - 05 June 2021
Date Added to IEEE Xplore: 18 October 2021
ISBN Information: