Consensus of Multi-Agent Systems using Back-tracking and History following Algorithms

Y. V. Karteek, I. Kar, S. Majhi
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引用次数: 3

Abstract

This paper proposes two algorithms, namely "back-tracking" and "history following", to reach consensus in case of communication loss for a network of distributed agents with switching topologies. To reach consensus in distributed control, considered communication topology forms a strongly connected graph. The graph is no more strongly connected whenever an agent loses communication.Whenever an agent loses communication, the topology is no more strongly connected. The proposed back-tracking algorithm makes sure that the agent backtracks its position unless the communication is reestablished, and path is changed to reach consensus. In history following, the agents use their memory and move towards previous consensus point until the communication is regained. Upon regaining communication, a new consensus point is calculated depending on the current positions of the agents and they change their trajectories accordingly. Simulation results, for a network of six agents, show that when the agents follow the previous history, the average consensus time is less than that of back-tracking. However, situation may arise in history following where a false notion of reaching consensus makes one of the agents stop at a point near to the actual consensus point. An obstacle avoidance algorithm is integrated with the proposed algorithms to avoid collisions. Hardware implementation for a three robots system shows the effectiveness of the algorithms.
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使用回溯和历史跟踪算法的多智能体系统的一致性
针对具有交换拓扑的分布式智能体网络,提出了“回溯”和“历史跟踪”两种算法,用于在通信丢失情况下达成共识。为了在分布式控制中达成共识,所考虑的通信拓扑构成了一个强连通图。当一个代理失去通信时,图不再是强连接的。当一个代理失去通信时,拓扑不再是强连接的。提出的回溯算法确保agent在通信不被重新建立的情况下回溯其位置,并且路径被改变以达成共识。在历史跟踪中,代理使用他们的记忆并向先前的共识点移动,直到通信恢复。在重新获得通信后,根据代理的当前位置计算新的共识点,并相应地改变它们的轨迹。仿真结果表明,对于由6个智能体组成的网络,当智能体遵循之前的历史时,平均共识时间小于回溯的时间。然而,历史上可能会出现这样的情况,即达成共识的错误概念使其中一个代理停止在接近实际共识点的一点。将避障算法与所提算法相结合以避免碰撞。三机器人系统的硬件实现验证了算法的有效性。
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