用群体智能原则控制群机器人搜索

用群机器人搜索定位矿难幸存者,可为人工施救提供决策参考.群机器人系统的建模基于个体有限感知和局部交互等群体智能原则,将机器人抽象为封闭2维空间的运动粒子,机器人与控制器综合抽象为一阶惯性环节.给出了机器人的感知函数、邻域结构及初始化区域的定义,以此为基础进行虚拟多agent搜索.针对机器人的最大运动速度和质量惯性等约束,交替施加螺旋控制以发现信号线索;施加扩展微粒群控制进行目标搜索.通过改变通信距离和感知范围进行了仿真实验,结果表明了控制策略的有效性.

Control over Swarm Robots Search with Swarm Intelligence Principles

Swarm robots possess the potential to save lives by providing the rescuers location of victim during the most critical early hours in coal mine disaster areas. Robot and its controller as an inertial element and modeled such distributed system at an abstract level were viewed according to the swarm intelligence principles,which used a virtual multi-agents search to locate the target in a closed 2-D space. The control over robots was attributed to two kinds:moving spirally to search for cues and extending particle swarm optimization to search for target. The former is to offer evidence for the latter working. Then the definitions of sensing function,neighborhood structure and initiating area of robots were given. Taking the limited sense ability and local interaction mechanism into account,the properties of the system were obtained by changing different parameters such as number of robots,communication range and sense scope in simulating experiment. The simulation results indicate validity of the control strategy.