Flocking for Multiple Ellipsoidal Agents with Limited Communication Ranges

This paper contributes a design of distributed controllers for flocking of mobile agents with an ellipsoidal shape and a limited communication range. A separation condition for ellipsoidal agents is first derived. Smooth step functions are then introduced. These functions and the separation condition between the ellipsoidal agents are embedded in novel pairwise potential functions to design flocking control algorithms. The proposed flocking design results in (1) smooth controllers despite of the agents’ limited communication ranges, (2) no collisions between any agents, (3) asymptotic convergence of each agent’s generalized velocity to a desired velocity, and (4) boundedness of the flock size, defined as the sum of all distances between the agents, by a constant.

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Control of Multiple Mobile Agents Via Artificial Potential Functions and Random Motion

Volume 9: Mechanical Systems and Control, Parts A, B, and C ◽

10.1115/imece2007-41521 ◽

2007 ◽

Cited By ~ 1

Author(s):

Manish Kumar ◽

Devendra P. Garg ◽

Randy Zachery

Keyword(s):

Potential Function ◽

Mobile Agents ◽

Formation Control ◽

Cluster Formation ◽

Limited Range ◽

Random Motion ◽

Potential Functions ◽

Random Behavior ◽

Artificial Potential Function ◽

Multiple Mobile Agents

This paper investigates the effectiveness of designed random behavior in cooperative formation control of multiple mobile agents. A method based on artificial potential functions provides a framework for decentralized control of their formation. However, it implies heavy communication costs. The communication requirement can be replaced by onboard sensors. The onboard sensors have limited range and provide only local information, and may result in the formation of isolated clusters. This paper proposes to introduce a component representing random motion in the artificial potential function formulation of the formation control problem. The introduction of the random behavior component results in a better chance of global cluster formation. The paper uses an agent model that includes both position and orientation, and formulates the dynamic equations to incorporate that model in artificial potential function approach. The effectiveness of the proposed method is verified via extensive simulations performed on a group of mobile agents and leaders.

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Formation control of mobile agents using local potential functions

2006 American Control Conference ◽

10.1109/acc.2006.1656537 ◽

2006 ◽

Cited By ~ 9

Author(s):

K.D. Do

Keyword(s):

Mobile Agents ◽

Formation Control ◽

Potential Functions ◽

Local Potential

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Evacuation of Equilateral Triangles by Mobile Agents of Limited Communication Range

Algorithms for Sensor Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-030-34405-4_1 ◽

2019 ◽

pp. 3-22 ◽

Cited By ~ 1

Author(s):

Iman Bagheri ◽

Lata Narayanan ◽

Jaroslav Opatrny

Keyword(s):

Mobile Agents ◽

Communication Range ◽

Limited Communication ◽

Equilateral Triangles

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Mobile Agents: Control Algorithms

10.1007/10704127 ◽

2000 ◽

Cited By ~ 9

Author(s):

Joachim Baumann

Keyword(s):

Mobile Agents ◽

Control Algorithms

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MARS: An Educational Environment for Multiagent Robot Simulations

Modelling and Simulation in Engineering ◽

10.1155/2016/5914706 ◽

2016 ◽

Vol 2016 ◽

pp. 1-13

Author(s):

Marco Casini ◽

Andrea Garulli

Keyword(s):

User Interface ◽

Mobile Robots ◽

Graphical User Interface ◽

Educational Environment ◽

Control Algorithms ◽

Virtual Sensors ◽

Multirobot Teams ◽

Distributed Controllers ◽

Time To Learn

Undergraduate robotics students often find it difficult to design and validate control algorithms for teams of mobile robots. This is mainly due to two reasons. First, very rarely, educational laboratories are equipped with large teams of robots, which are usually expensive, bulky, and difficult to manage and maintain. Second, robotics simulators often require students to spend much time to learn their use and functionalities. For this purpose, a simulator of multiagent mobile robots namedMARShas been developed within the Matlab environment, with the aim of helping students to simulate a wide variety of control algorithms in an easy way and without spending time for understanding a new language. Through this facility, the user is able to simulate multirobot teams performing different tasks, from cooperative to competitive ones, by using both centralized and distributed controllers. Virtual sensors are provided to simulate real devices. A graphical user interface allows students to monitor the robots behaviour through an online animation.

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An exactly soluble three-body problem in one dimension

Canadian Journal of Physics ◽

10.1139/p80-098 ◽

1980 ◽

Vol 58 (6) ◽

pp. 719-728 ◽

Cited By ~ 21

Author(s):

C. Jung

Keyword(s):

Closed Form ◽

Bound States ◽

Body Problem ◽

Potential Functions ◽

One Dimension ◽

Three Body Problem ◽

One Dimensional ◽

Continuum States ◽

Step Functions ◽

Three Body

An exactly soluble one-dimensional three-body problem is presented, in which the interaction between the particles consists of local two-body potentials between each two particles. Infinitely high step functions are chosen for the form of the three potential functions. This interaction allows only three-body bound states and no continuum states. We have considered three different choices of the mass ratios of the three particles and we give formulas in closed form for the energies and for the wavefunctions of all states.

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