13,775 research outputs found
A Distributed Epigenetic Shape Formation and Regeneration Algorithm for a Swarm of Robots
Living cells exhibit both growth and regeneration of body tissues. Epigenetic
Tracking (ET), models this growth and regenerative qualities of living cells
and has been used to generate complex 2D and 3D shapes. In this paper, we
present an ET based algorithm that aids a swarm of identically-programmed
robots to form arbitrary shapes and regenerate them when cut. The algorithm
works in a distributed manner using only local interactions and computations
without any central control and aids the robots to form the shape in a
triangular lattice structure. In case of damage or splitting of the shape, it
helps each set of the remaining robots to regenerate and position themselves to
build scaled down versions of the original shape. The paper presents the shapes
formed and regenerated by the algorithm using the Kilombo simulator.Comment: 8 pages, 9 figures, GECCO-18 conferenc
COORDINATION OF LEADER-FOLLOWER MULTI-AGENT SYSTEM WITH TIME-VARYING OBJECTIVE FUNCTION
This thesis aims to introduce a new framework for the distributed control of multi-agent systems with adjustable swarm control objectives. Our goal is twofold: 1) to provide an overview to how time-varying objectives in the control of autonomous systems may be applied to the distributed control of multi-agent systems with variable autonomy level, and 2) to introduce a framework to incorporate the proposed concept to fundamental swarm behaviors such as aggregation and leader tracking. Leader-follower multi-agent systems are considered in this study, and a general form of time-dependent artificial potential function is proposed to describe the varying objectives of the system in the case of complete information exchange. Using Lyapunov methods, the stability and boundedness of the agents\u27 trajectories under single order and higher order dynamics are analyzed. Illustrative numerical simulations are presented to demonstrate the validity of our results. Then, we extend these results for multi-agent systems with limited information exchange and switching communication topology. The first steps of the realization of an experimental framework have been made with the ultimate goal of verifying the simulation results in practice
Collective behaviour without collective order in wild swarms of midges
Collective behaviour is a widespread phenomenon in biology, cutting through a
huge span of scales, from cell colonies up to bird flocks and fish schools. The
most prominent trait of collective behaviour is the emergence of global order:
individuals synchronize their states, giving the stunning impression that the
group behaves as one. In many biological systems, though, it is unclear whether
global order is present. A paradigmatic case is that of insect swarms, whose
erratic movements seem to suggest that group formation is a mere epiphenomenon
of the independent interaction of each individual with an external landmark. In
these cases, whether or not the group behaves truly collectively is debated.
Here, we experimentally study swarms of midges in the field and measure how
much the change of direction of one midge affects that of other individuals. We
discover that, despite the lack of collective order, swarms display very strong
correlations, totally incompatible with models of noninteracting particles. We
find that correlation increases sharply with the swarm's density, indicating
that the interaction between midges is based on a metric perception mechanism.
By means of numerical simulations we demonstrate that such growing correlation
is typical of a system close to an ordering transition. Our findings suggest
that correlation, rather than order, is the true hallmark of collective
behaviour in biological systems.Comment: The original version has been split into two parts. This first part
focuses on order vs. correlation. The second part, about finite-size scaling,
will be included in a separate paper. 15 pages, 6 figures, 1 table, 5 video
Safe, Remote-Access Swarm Robotics Research on the Robotarium
This paper describes the development of the Robotarium -- a remotely
accessible, multi-robot research facility. The impetus behind the Robotarium is
that multi-robot testbeds constitute an integral and essential part of the
multi-agent research cycle, yet they are expensive, complex, and time-consuming
to develop, operate, and maintain. These resource constraints, in turn, limit
access for large groups of researchers and students, which is what the
Robotarium is remedying by providing users with remote access to a
state-of-the-art multi-robot test facility. This paper details the design and
operation of the Robotarium as well as connects these to the particular
considerations one must take when making complex hardware remotely accessible.
In particular, safety must be built in already at the design phase without
overly constraining which coordinated control programs the users can upload and
execute, which calls for minimally invasive safety routines with provable
performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference
Formation control of a group of micro aerial vehicles (MAVs)
Coordinated motion of Unmanned Aerial Vehicles (UAVs) has been a growing research interest in the last decade. In this paper we propose a coordination model that makes use of virtual springs and dampers to generate reference trajectories for a group of quadrotors. Virtual forces exerted on each vehicle are produced by using projected distances between the quadrotors. Several coordinated task scenarios are presented and the performance of the proposed method is verified by simulations
sUAS Swarm Navigation using Inertial, Range Radios and Partial GNSS
Small Unmanned Aerial Systems (sUAS) operations are increasing in demand and complexity. Using multiple cooperative sUAS (i.e. a swarm) can be beneficial and is sometimes necessary to perform certain tasks (e.g., precision agriculture, mapping, surveillance) either independent or collaboratively. However, controlling the flight of multiple sUAS autonomously and in real-time in a challenging environment in terms of obstacles and navigation requires highly accurate absolute and relative position and velocity information for all platforms in the swarm. This information is also necessary to effectively and efficiently resolve possible collision encounters between the sUAS. In our swarm, each platform is equipped with a Global Navigation Satellite System (GNSS) sensor, an inertial measurement unit (IMU), a baro-altimeter and a relative range sensor (range radio). When GNSS is available, its measurements are tightly integrated with IMU, baro-altimeter and range-radio measurements to obtain the platform’s absolute and relative position. When GNSS is not available due to external factors (e.g., obstructions, interference), the position and velocity estimators switch to an integrated solution based on IMU, baro and relative range meas-urements. This solution enables the system to maintain an accurate relative position estimate, and reduce the drift in the swarm’s absolute position estimate as is typical of an IMU-based system.
Multiple multi-copter data collection platforms have been developed and equipped with GNSS, inertial sensors and range radios, which were developed at Ohio University. This paper outlines the underlying methodology, the platform hardware components (three multi-copters and one ground station) and analyzes and discusses the performance using both simulation and sUAS flight test data
Implementation of UAV Coordination Based on a Hierarchical Multi-UAV Simulation Platform
In this paper, a hierarchical multi-UAV simulation platform,called XTDrone,
is designed for UAV swarms, which is completely open-source 4 . There are six
layers in XTDrone: communication, simulator,low-level control, high-level
control, coordination, and human interac-tion layers. XTDrone has three
advantages. Firstly, the simulation speedcan be adjusted to match the computer
performance, based on the lock-step mode. Thus, the simulations can be
conducted on a work stationor on a personal laptop, for different purposes.
Secondly, a simplifiedsimulator is also developed which enables quick algorithm
designing sothat the approximated behavior of UAV swarms can be observed
inadvance. Thirdly, XTDrone is based on ROS, Gazebo, and PX4, andhence the
codes in simulations can be easily transplanted to embeddedsystems. Note that
XTDrone can support various types of multi-UAVmissions, and we provide two
important demos in this paper: one is aground-station-based multi-UAV
cooperative search, and the other is adistributed UAV formation flight,
including consensus-based formationcontrol, task assignment, and obstacle
avoidance.Comment: 12 pages, 10 figures. And for the, see
https://gitee.com/robin_shaun/XTDron
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