Formation control based on artificial intelligence for multi-agent coordination

Seong-woo Hong, S. Shin, D. Ahn
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引用次数: 12

Abstract

In this paper, the authors propose a method of cooperative control based on an artificially intelligent system in a distributed autonomous robotic system. In general, a multi-agent behavior algorithm is simple and effective for small number of robots. However, as the number of robots increases, this becomes difficult to realize because a multi-robot behavior algorithm requires multiple constraints and goals in mobile robot navigation problems. As the solution to the above problem, the authors propose an architecture of a fuzzy-neuro system for obstacle avoidance. The controller adopts a simple reactive navigation strategy by combining repulsion from obstacles with attraction to a goal. Simulation results shows that the proposed strategy is effective for multi-robot to avoid obstacles while maintaining a formation.
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基于人工智能的多智能体协调编队控制
在分布式自主机器人系统中,提出了一种基于人工智能系统的协同控制方法。一般来说,多智能体行为算法对于少量机器人是简单有效的。然而,随着机器人数量的增加,由于多机器人行为算法在移动机器人导航问题中需要多个约束和目标,这就变得难以实现。为了解决上述问题,作者提出了一种模糊神经避障系统的结构。控制器采用简单的响应式导航策略,将障碍物的斥力与目标的吸引力结合起来。仿真结果表明,该策略对于多机器人在保持队形的同时避开障碍物是有效的。
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