摘要
为提高多机器人在未知环境中的探测效率,文中提出基于生物熵的免疫协作探测算法。该算法首先根据生物熵原理计算抗原激励;其次综合抗原激励与抗体浓度来确定最佳探测栅格;最后针对机器人在探测过程中的“被锁”情况,利用“记忆细胞”进行“解锁”,并采用“插补法”快速移动到记忆细胞中目标点。不同环境中实验测试结果表明:与完全探测算法相比,文中算法的探测步数平均降低了11.84%,重复探测步数平均降低59.10%,重复探测率平均降低53.91%,充分体现了多机器人免疫协作探测的合理性和有效性。
In order to improve the detection efficiency of Multi-robot in unknown environments,an immune cooperative detection algorithm based on biological entropy is proposed in the text.The antigen excitation value is first calculated in this algorithm according to the principle of biological entropy,then the optimal detection grid is determined by combining antigen excitation and antibody concentration.Finally,aiming at the“locked”situation of the robot in the detection process,the“memory cell”is used to“unlock”,and the“interpolation method”is used to quickly move to the target point in the“memory cell”.The result of multiple experiments in different environments have shown that compared with the full detection algorithm,the detection steps in the proposed algorithm are reduced by an average of 11.84%,the repeated detection steps are reduced by an average of 59.10%,and the repetition detection rate is reduced by an average of 53.91%.The rationality and effectiveness are fully embodied in multi-robot immune cooperative detection.
作者
陈一鸣
申燚
黄艇
姜烽
袁明新
CHEN Yi-ming;SHEN Yi;HUANG Ting;JIANG Feng;YUAN Ming-xin(School of Mechanics and Power Engineering,Jiangsu University of Science and Technology,Zhangjiagang 215600,Jiangsu Province,China;Zhangjiagang Industrial Technology Research Institute,Jiangsu University of Science and Technology,Zhangjiagang 215600,Jiangsu Province,China)
出处
《信息技术》
2019年第12期1-5,共5页
Information Technology
基金
国家自然科学基金(61105071)
关键词
生物熵
免疫系统
多机器人
协作探测
biological entropy
immune system
multi-robot
collaborative detection
