Formation flying control via elliptical virtual structure

Kahn, Arthur B.; Marzat, Julien; Piet-Lahanier, Hélène

doi:10.1109/icnsc.2013.6548729

Cited by 6 publications

(4 citation statements)

References 20 publications

(10 reference statements)

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“…The positions of the robots in the swarm are defined with respect to a reference point in the structure. As the trajectory for the reference point is predefined, the desired trajectory for each robots is calculated as the rigid body evolves in time [12,16,18,26,33]. The main advantages of this approach is that a single mathematical rule governs the robot's behavior.…”

Section: Related Workmentioning

confidence: 99%

Realization of Lattice Formation in Nonlinear Two-dimensional Potential by Mobile Robots

Wang¹,

Baba²,

Hikihara³

2022

Preprint

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Formation control in multi-agent system has earned significant research interests in both theorical aspect and applications over the past two decades. However, the study on how the external environment shapes swarm formation dynamics, and the design of formation control algorithm for multi-agent system in nonlinear external potential have not been rigorously investigated. In this paper, we present a formation control algorithm for mobile robots travelling in nonlinear external potential. Experiments are performed on real mobile robots to verify the algorithm, and the effectiveness of Dynamical Mode Decomposition in robot's velocity prediction in unknown environment is demonstrated.

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Section: Related Workmentioning

confidence: 99%

Realization of Lattice Formation in Nonlinear Two-dimensional Potential by Mobile Robots

Wang¹,

Baba²,

Hikihara³

2022

Preprint

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“…The third category of methods hinges upon virtual geometrical structures in which the swarm of agents should remain globally. The control law must first ensure that the agents are located within the structure and then define a suitable structure evolution depending on the mission requirements [9,10]. A common approach is to design potential fields and navigation functions that are sometimes difficult to construct with good properties (differentiable, without multiple critical points).…”

Section: Introductionmentioning

confidence: 99%

Distributed Control for Multi-Robot Interactive Swarming Using Voronoi Partioning

Eudes,

Bertrand,

Marzat

et al. 2023

Drones

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The problem of safe navigation of a human-multi-robot system is addressed in this paper. More precisely, we propose a novel distributed algorithm to control a swarm of unmanned ground robots interacting with human operators in presence of obstacles. Contrary to many existing algorithms that consider formation control, the proposed approach results in non-rigid motion for the swarm, which more easily enables interactions with human operators and navigation in cluttered environments. Each vehicle calculates distributively and dynamically its own safety zone in which it generates a reference point to be tracked. The algorithm relies on purely geometric reasoning through the use of Voronoi partitioning and collision cones, which allows to naturally account for inter-robot, human-robot and robot-obstacle interactions. Different interaction modes have been defined from this common basis to address the following practical problems: autonomous waypoint navigation, velocity-guided motion, and follow a localized operator. The effectiveness of the algorithm is illustrated by outdoor and indoor field experiments.

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“…A controller is an essential structure that is used in the implementation and simulation of swarm systems [15]. There are three main approaches to formation control systems [4,12,16]: the leader-follower approach [12,[17][18][19], the virtual structure approach [1,20,21], and the behavior-based approach [5,14,16,[22][23][24][25][26]. Despite the simplicity of the leader-follower approach, it may suffer from being highly dependent on the leader agent and from the large amount of information exchange required between the leader and each of the followers due to being a centralized system [4].…”

Section: Introductionmentioning

confidence: 99%

Effect of Formation Size on Flocking Formation Performance for the Goal Reach Problem

et al. 2022

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Flocking is one of the swarm tasks inspired by animal behavior. A flock involves multiple agents aiming to achieve a goal while maintaining certain characteristics of their formation. In nature, flocks vary in size. Although several studies have focused on the flock controller itself, less research has focused on how the flock size affects flock formation and performance. In this study, we address this problem and develop a simple flock controller for goal-zone-reaching tasks. The developed controller is intended for a two-dimensional environment and can handle obstacles as well as integrate an additional invented feature, called sensing power, in order to simulate the natural dynamics of migratory birds. This controller is simulated using the NetLogo simulation tool. Several experiments were conducted with and without obstacles, accompanied by changes in the flock size. The simulation results demonstrate that the flock controller is able to successfully deliver the flock to the goal zone. In addition, changes in the flock size affect multiple metrics, such as the time required to reach the goal (and, consequently, the time required to complete the flocking task), as well as the number of collisions that occur.

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Formation flying control via elliptical virtual structure

Cited by 6 publications

References 20 publications

Realization of Lattice Formation in Nonlinear Two-dimensional Potential by Mobile Robots

Realization of Lattice Formation in Nonlinear Two-dimensional Potential by Mobile Robots

Distributed Control for Multi-Robot Interactive Swarming Using Voronoi Partioning

Effect of Formation Size on Flocking Formation Performance for the Goal Reach Problem

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