基于二次Bezier曲线的无线传感网避障路径规划研究

Obstacles Avoidance Based Quadratic Bezier Curve Path Planning for Wireless Sensor Networks

用固定Sink节点进行无线传感网内数据采集的传统方式会导致热点区域(hot spot)问题,而采用移动Sink节点进行数据采集可以克服这个问题,从而达到均衡网络能量分布与延长网络生命周期的效果。本文针对类车型机器人作为无线传感网中移动数据汇聚节点的应用场景,提出了一种基于Bezier连续曲线的移动Sink节点避障路径规划算法。本文构建了连续分段Bezier曲线为巡航轨迹,采用人工势场中的斥力场理论实现对多个障碍物的智能躲避,动态调节二次Bezier曲线的内部控制点位置,将障碍物排斥在二次Bezier曲线之外。仿真结果验证本文提出的算法可以实现移动Sink节点规划路径的避障功能,同时Bezier曲线规划算法简单,计算量较小。

The traditional sensory data collection method with fixed Sink node will lead to hot spot problem. To overcome this problem,mobile data collection by mobile Sink is proposed so as to balance network energy distribution and prolong network lifecycle. Aiming at the application scenario of the vehicle-like robot as a mobile data aggregation node in wireless sensor networks,this paper proposes a continuous quadratic Bezier curves based obstacle avoidance path planning algorithm for mobile Sink node. Firstly,some segmented continuous Bezier curves are constructed as a whole cruise trajectory. Secondly,the repulsive effect of multiple obstacles is analyzed by artificial potential field method. As a result,the position of internal control points of Bezier curve is dynamically adjusted with repulsive potential field,and adjacent obstacles can be excluded from delta-shaped region by quadratic Bezier curve.Simulation results verify that the proposed method can realize multiple obstacles avoidance in the planning path of mobile Sink node with smaller computational complexity.