自适应缓冲控制的移动机器人分布式多跳路由算法

针对移动机器人平台下60GHz无线信号太弱而无法存在于高衰减的长距离或非直线环境的问题,提出了一种基于自适应缓冲控制的分布式鲁棒多跳路由算法。该算法的核心思想是通过求解单位时间平均预期功耗总和最小化和每单位时隙缓冲稳定性的联合随机优化来确定功率分配量,使每个机器人平台能够计算从它自己的缓冲区传输数据包的功率分配量,从而优化整个系统。拥有二十个移动监控机器人平台的仿真实验验证了提出的算法的有效性。实验结果表明,相比分布式多跳路由协议中较为著名的自组织网络按需距离向量(AODV)算法,提出的算法在平均功耗和缓冲占有率方面均有优势,在权重因子为0.5和2时,缓冲占有率分别为AODV的0.14和0.34倍,平均功耗也有所降低。

A distributed multi-hop routing algorithm based on adaptive buffer controlling for robot

As 60GHz wireless signal is too weak, this cannot exist in the high-attenuation over long distance or non-linear environment. A distributed robust multi-hop routing algorithm based on adaptive buffer control is proposed. The core idea is that the joint stochastic optimization by solving average expected sum of the power consumption in unit time and the stability of the power distribution per unit of time is to decide the power allocation, so that each robot platform can be calculated from the amount of its own power allocation transmission packet buffer. And the system can be optimized. Simulations that have twenty mobile surveillance robot platforms verify the effectiveness of the proposed algorithm. Experimental results show that, compared to Ad-hoc on-demand distance vector routing (AODV), which is quite famous in distributed multi-hop routing protocols, the proposed algorithm has advantages in both aspects of average power consumption and buffer occupancy. The buffer occupancy is 0.14 and 0.34 times than that of AODV respectively in the weighting factor of 0.5 and 2. And the average power consumption is also reduced.