AGDS: adaptive goal-directed strategy for swarm drones flying through unknown environments

Abstract

This paper aims to address a challenging problem of a drone swarm for a specific mission by reaching a desired region, through an unknown environment. A bio-inspired flocking algorithm with adaptive goal-directed strategy (AGDS) is proposed and developed for the drones swarmed across unknown environments. Each drone employs a biological visual mechanism to sense obstacles in within local perceptible scopes. Task information of the destination is only given to a few specified drones (named as informed agents), rather than to all other individual drones (uninformed agents). With the proposed flocking swarm, the informed agents operate collectively with the remaining uninformed agents to achieve a common and overall mission. By virtue of numerical simulation, the AGDS and non-adaptive goal-directed strategy (non-AGDS) are both presented and evaluated. Experiments by flying six DJI Tello quadrotors indoor are conducted to validate the developed flocking algorithm. Additional validations within canyon-like complicated scenarios have also been carried out. Both simulation and experimental results demonstrate the efficiency of the proposed swarm flocking algorithm with AGDS.

ATI: Assemble topological interaction overcomes consistency–cohesion trade‐off in bird flocking

“…In addition, the presence of downwash airflow from rotors can impact neighbouring drones beneath a quadcopter, potentially leading to a loss of control. Thus, most studies [19,[25][26][27] maintain a fixed altitude for all drones and concentrate on controlling horizontal movements using swarm models or algorithms. The same applies to this paper.…”

“…Repulsion behaviour prevents excessive closeness, and attraction behaviour prevents individuals from being too far apart from neighbours. Since then, many models have been built based on these three rules and metric interactions, incorporating additional behavioural rules to replicate various collective behaviours, such as group chasing [17], collective navigation [10, 18, 19], collective shepherding [20], anti‐predatory [21, 22]. Among them, Couzin et al .‘s work [10] on collective navigation is closely related to this paper.…”