Multi-robot coalition formation in real-time scenarios

José Guerrero; Gabriel Oliver

doi:10.1016/j.robot.2012.06.004

Multi-robot coalition formation in real-time scenarios

Robotics and Autonomous Systems ◽

10.1016/j.robot.2012.06.004 ◽

2012 ◽

Vol 60 (10) ◽

pp. 1295-1307 ◽

Cited By ~ 28

Author(s):

José Guerrero ◽

Gabriel Oliver

Keyword(s):

Real Time ◽

Coalition Formation ◽

Multi Robot

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A real-time heterogeneous distributed computing environment for multi-robot system

Proceedings Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC 2000) (Cat. No. PR00607) ◽

10.1109/isorc.2000.839554 ◽

2002 ◽

Author(s):

K. Qutubudin ◽

D. Pease

Keyword(s):

Distributed Computing ◽

Real Time ◽

Computing Environment ◽

Robot System ◽

Heterogeneous Distributed Computing ◽

Multi Robot

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Distributed Hedonic Coalition Formation for Multi-Robot Task Allocation

10.1109/case49439.2021.9551582 ◽

2021 ◽

Author(s):

Ayan Dutta ◽

Vladimir Ufimtsev ◽

Tuffa Said ◽

Inmo Jang ◽

Roger Eggen

Keyword(s):

Coalition Formation ◽

Task Allocation ◽

Robot Task ◽

Hedonic Coalition Formation ◽

Multi Robot

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Multi-Robot Searching using Game-Theory Based Approach

International Journal of Advanced Robotic Systems ◽

10.5772/6232 ◽

2008 ◽

Vol 5 (4) ◽

pp. 44 ◽

Cited By ~ 17

Author(s):

Yan Meng

Keyword(s):

Game Theory ◽

Dynamic Programming ◽

Utility Function ◽

Real Time ◽

Dynamic Environment ◽

Equilibrium Solutions ◽

Strategy Equilibrium ◽

The Game Theory ◽

Target Searching ◽

Multi Robot

This paper proposes a game-theory based approach in a multi–target searching using a multi-robot system in a dynamic environment. It is assumed that a rough priori probability map of the targets' distribution within the environment is given. To consider the interaction between the robots, a dynamic-programming equation is proposed to estimate the utility function for each robot. Based on this utility function, a cooperative nonzero-sum game is generated, where both pure Nash Equilibrium and mixed-strategy Equilibrium solutions are presented to achieve an optimal overall robot behaviors. A special consideration has been taken to improve the real-time performance of the game-theory based approach. Several mechanisms, such as event-driven discretization, one-step dynamic programming, and decision buffer, have been proposed to reduce the computational complexity. The main advantage of the algorithm lies in its real-time capabilities whilst being efficient and robust to dynamic environments.

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