障碍物与多目标约束下主动传感器网络自组织运动规划

摘要

In order to solve the problem of motion planning for self-organization of an active sensor network under the constraints of obstacle environment and multi-target,a collision-free path planning algorithm is presented in the paper.Firstly,a multi-objective selection mechanism based on auction algorithm is designed to convert the target value and the distance cost into profits,which achieves the goal of maximizing the system benefits.An improved rapidly-exploring random tree (RRT) algorithm is proposed for each sensor node based on its own target.Compared with the traditional RRT algorithm,the improved RRT algorithm introduces a heuristic evaluation function to reduce some needless trajectory paths and reduces the path planning time.Finally,under different obstacle environments,the simulations of the path planning of the active sensor networks are provided to verify the superiority of the proposed algorithms.%为解决障碍物环境与多目标约束下主动传感器网络自组织运动规划问题,提出了一种分阶段无碰撞运动规划方法.首先,将目标价值及距离代价转化为收益,以系统收益最大为目标,设计了一种基于拍卖算法的多目标选择机制.在每个传感器节点选择各自目标基础上,提出一种改进的快速扩展随机树算法.相比于传统的快速扩展随机树算法,所提出的改进算法引入了启发式函数,减少了不必要的轨迹路径,进而降低轨迹规划时间.最后,给出了主动传感器网络在不同障碍环境下的规划路径,验证了所提算法的优越性.