摘要
针对多智能体编队通过障碍物区域的避撞和避障问题,利用传感器的监控功能,采用改进的人工势能场法对避障算法进行优化,使多智能体编队能有效地通过障碍物区域,并在通过障碍物区域后再次形成多智能体编队。首先,从多智能体模型上进行改进,建立一种具有可视化范围的速度为矢量的速度可变的智能体模型。然后,使用矢量的人工势能场法进行多智能体编队的避撞和避障。最后,针对多智能体编队避障过程中会存在"局部困扰"的情况,加入"回环力"使多智能体编队能够通过障碍物区域,并在通过障碍物区域后继续编队运行。同时,使用MATLAB软件在坐标系中进行多智能体编队的避障仿真,验证了改进人工势能场法的有效性和正确性,为多智能体编队避障问题提供了更加有效的方法。
In order to solve the collision avoidance and obstacle avoidance problem according to Multi-Agent formation through the obstacles area,an obstacle avoidance algorithm is optimized by the improved artificial potential field method,the Multi-Agent formation can effectively pass the obstacles area,and after passed the obstacles area,the Multi-Agent formed again. First,the Multi-Agent model is improved,Agent model is built based on the speed vector with a visualization range of speed. Then,the obstacle avoidance problem of Multi-Agent is solved using the Vectorial Artificial Potential Field（VAPF） method. Finally,by adding ＂ rotational force＂ to the force of agent,the agents can easily pass the obstacles area,and solve the ＂ local trouble＂. Simulation results verify the efficiency and validity of the method.
出处
《计算机仿真》
CSCD
北大核心
2015年第3期388-392,共5页
Computer Simulation
基金
国家自然科学基金(61164015)
2013年南昌航空大学研究生创新专项资金(YC2013-014)
关键词
多智能体编队
矢量人工势能场法
避障问题
局部困扰
回环力
Multi-agent formation
Vectorial artificial potential field method
Obstacle avoidance problem
Local trouble
Rotational force
