基于简化虚拟受力模型的群机器人多目标搜索协调控制

发布时间：2019-05-28 10:26

【摘要】：针对未知凸和非凸障碍物以及动态障碍物环境下群机器人多目标搜索问题,提出了一种基于简化虚拟受力分析模型的循障和避碰方法(SRSMT-SVF).对复杂环境下群机器人多目标搜索行为进行了分解并抽象出简化虚拟受力分析模型.基于此受力模型,设计了个体机器人协同搜索和漫游状态下的运动控制策略,使得机器人在搜索目标的同时能够实时避碰.通过对不同群体规模系统的仿真实验表明,本文控制方法能够使个体机器人在整个搜索过程中保持良好的避碰性能,有效地减少系统与环境之间和系统内部个体之间的碰撞冲突.相比于扩展粒子群算法(EPSO),本文方法使得搜索耗时和系统能耗至少减少了13.78%、11.96%,数值仿真结果验证了本文方法的有效性.
[Abstract]:In order to solve the multi-objective search problem of group robots in unknown convex and non-convex obstacles and dynamic obstacle environments, a obstacle and collision avoidance method (SRSMT-SVF) based on simplified virtual force analysis model is proposed. The multi-objective search behavior of group robots in complex environment is decomposed and the simplified virtual force analysis model is abstracted. Based on this force model, the motion control strategy of individual robot in cooperative search and roaming state is designed, so that the robot can avoid collision in real time while searching for the target. The simulation results of different group scale systems show that the control method can make the individual robot maintain good collision avoidance performance in the whole search process. Effectively reduce collision conflicts between the system and the environment and between individuals within the system. Compared with the extended particle swarm optimization (EPSO),) method, the search time and system energy consumption are reduced by at least 13.78% and 11.96%. The numerical simulation results verify the effectiveness of the proposed method.
【作者单位】：湖南科技大学信息与电气工程学院;湖南理工职业技术学院;
【基金】：国家自然科学基金(51374107,51577057) “十二五”国防基础科技计划(B3720110008) 湖南省自然科学基金(13JJ8014)
【分类号】：TP242

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