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Investigating the Rate of Failure of Asynchronous Gathering in a Swarm of Fat Robots with Limited Visibility

机译:调查具有有限可见性的大量肥胖机器人中异步聚集的失败率

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In the present paper we investigate the failure probability of the asynchronous gathering task in a mobile robot swarm that contains weak robots (oblivious, with limited visibility, without global navigation and communication). We are modelling fat robots, which are represented as solid discs. We performed numerous computer simulations in order to measure the rate of failure of gathering using extended Ando's gathering algorithm. The physical parameters of the simulations are based on our previous experiments on image processing based kin recognition method using Surveyor SRV-1 robots. It was obtained that the computational time and the travelling speed of the robots affect very strongly the rate of gathering success. If we apply SRV-1 robots with the referred kin recognition method and highest possible travelling speed, then the rate of failure is very close to 100 percent. While, reducing the travelling speed with a factor of 1/20 (or increasing the computational performance to 20 times the original) results in much better success rates of gathering. Besides, we have found that the failure rate increases together with the number of robots.
机译:在本文中,我们研究了包含弱机器人(明显,可见性有限,没有全局导航和通信)的移动机器人群中异步收集任务的失败概率。我们正在建模胖机器人,以实心圆盘表示。为了测量使用扩展的Ando收集算法的收集失败率,我们进行了许多计算机模拟。模拟的物理参数基于我们之前使用Surveyor SRV-1机器人进行基于图像处理的亲属识别方法的实验。可以看出,机器人的计算时间和行进速度会极大地影响采集成功的速度。如果我们将SRV-1机器人应用到所提及的亲属识别方法和尽可能高的行驶速度,那么故障率将非常接近100%。同时,将行进速度降低1/20倍(或将计算性能提高到原始速度的20倍)可以提高采集的成功率。此外,我们发现故障率随着机器人数量的增加而增加。

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