煤巷掘进机纠偏路径随机约束环境建模研究
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摘要
针对掘进机巷道实际路径规划背景下存在许多非结构性环境属性问题,本文将巷道非结构环境下的路径规划问题归类为一般性随机网络问题。文中分析了非结构环境的属性及行为约束,定义了包含约束信息的随机栅格网络模型,提出了最小耗费代价建模方法,利用遗传变异粒子群算法优化最佳路径目标点集。仿真和实验表明,文中提出的模型和算法能够有效解决随机网络最小耗费代价下井巷工程掘进机路径规划问题,其收敛速度和精度满足掘进机纠偏路径规划要求,验证了该方法在本文路径规划中的有效性与实用性。
Aiming at path planning problem of the unstructured environment attributions for roadheader roadway this paper analyzes the attributes and behavior constraints of unstructured environments,and a dynamic random grid network model with constraint information was defined(C-G Net).The minimum cost modeling method was proposed by optimization of best path target point set through improved VSAPSO algorithm.Results shows that the model and algorithm proposed in this paper could effectively solve the problem of network path planning under dynamic random with minimum cost roadheader excavation.Its convergence rate and advance rate meet the requirements of roadheader rectification path planning,and the effectiveness and practicability of this method were verified.
Aiming at path planning problem of the unstructured environment attributions for roadheader roadway this paper analyzes the attributes and behavior constraints of unstructured environments,and a dynamic random grid network model with constraint information was defined(C-G Net).The minimum cost modeling method was proposed by optimization of best path target point set through improved VSAPSO algorithm.Results shows that the model and algorithm proposed in this paper could effectively solve the problem of network path planning under dynamic random with minimum cost roadheader excavation.Its convergence rate and advance rate meet the requirements of roadheader rectification path planning,and the effectiveness and practicability of this method were verified.
引文
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[2]周自维,李长乐,赵杰,等.复杂局部地形中的实时路径规划算法设计[J].哈尔滨工业大学学报,2014,46(8):65-71.Zhou Ziwei,Li Changle,Zhao Jie,et al.A real time path planning algorithm based on local complicated environment[J].Journal of Harbin Institute of Technology,2014,46(8):65-71.
[3]庄佳园,张磊,孙寒冰,等.应用改进随机树算法的无人艇局部路径规划[J].哈尔滨工业大学学报,2015,47(1):112-117.Zhuang Jiayuan,Zhang Lei,Sun Hanbing,et al.Improved rapidly-exploring random tree algorithm application in unmanned surface vehicle local path planning[J].Journal of Harbin Institute of Technology,2015,47(1):112-117.
[4]金飞虎,高会军,钟啸剑.自适应蚁群算法在空间机器人路径规划中的应用[J].哈尔滨工业大学学报,2010,42(7):1014-1018.Jin Feihu,Gao Huijun,Zhong Xiaojian.Research on path planning of robot using adaptive ant colony system[J].Journal of Harbin Institute of Technology,2010,42(7):1014-1018.
[5]陈超,唐坚,靳祖光,等.一种基于可视图法导盲机器人路径规划的研究[J].机械科学与技术,2014,33(4):490-495.Chen Chao,Tang Jian,Jin Zuguang,et al.A path planning algorithm for seeing eye robots based on V-Graph[J].Mechanical Science and Technology for Aerospace Engineering,2014,33(4):490-495.
[6]杨环,刘乃文,段会川.基于T-Graph算法的主题爬虫研究[J].计算机工程与设计,2014,35(9):3014-3017,3028.Yang Huan,Liu Naiwen,Duan Huichuan.Research on topical Crawler of T-Graph algorithm[J].Computer Engineering and Design,2014,35(9):3014-3017,3028.
[7]涂伟.基于Voronoi图的大规模物流车辆路径优化方法研究[D].武汉:武汉大学,2013.
[8]王伟,王华.基于约束人工势场法的弹载飞行器实时避障航迹规划[J].航空动力学报,2014,29(7):1738-1743.Wang Wei,Wang Hua.Real-time obstacle avoidance trajectory planning for missile borne air vehicle based on constrained artificial potential field method[J].Journal of Aerospace Power,2014,29(7):1738-1743.
[9]简毅,张月.移动机器人全局覆盖路径规划算法研究进展与展望[J].计算机应用,2014,34(10):2844-2849,2864.Jian Yi,Zhang Yue.Complete coverage path planning algorithm for mobile robot:progress and prospect[J].Journal of Computer Applications,2014,34(10):2844-2849,2864.
[10]Robert A,Moshe K.Robot motion planning on N-dimensional star worlds among moving obstacles[J].IEEE Transactions on Robotics and Automation.1998,14(2):320-325.
[11]Garcia-Fidalgo E,Ortiz A.Vision-based topological mapping and localization methods[J].Robotics and Autonomous Systems,2015,64:1-20.
[12]钟建冬.基于狭窄通道识别的机器人路径规划研究[D].上海:上海交通大学,2012.
[13]杨艳春,鲍劲松,金烨.一种真实感虚拟月面建模方法[J].系统仿真学报,2007,19(11):2515-2518.Yang Yanchun,Bao Jinsong,Jin Ye.Realistic virtual lunar surface simulation method[J].Journal of System Simulation,2007,19(11):2515-2518.
[14]邵凯.数字地形技术在环境规划设计中的应用[J].浙江大学学报:理学版,2010,37(3):348-353.Shao Kai.Digital terrain analysis for landscape planning&design[J].Journal of Zhejiang University:Science Edition,2010,37(3):348-353.
[15]Laubach S L,Burdick J W.An autonomous sensorbased path-planner for planetary microrovers[J].IEEEInternational Conference on Robotics and Automation,1999,1(1):347-354.
[16]程海源.移动机器人路径规划的蚁群算法研究[D].哈尔滨:哈尔滨工程大学,2013.
[17]岳荣刚,王少萍.基于混合整数线性规划的爬壁机器人路径规划[J].北京航空航天大学学报,2013,39(6):792-797.Yue Ronggang,Wang Shaoping.Path planning of a climbing robot using mixed intger linear programming[J].Journal of Beijing University of Aeronautics and Astronautics,2013,39(6):792-797.
[18]张伍,党兆龙,贾阳.月面数字地形构造方法研究[J].航天器环境工程,2008,25(4):5,9-13.Zhang Wu,Dang Zhaolong,Jia Yang.Constructing methods for lunar digital terrain[J].Spacecraft Environment Engineering,2008,25(4):5,9-13.
[19]史美萍,吴军,李焱,等.面向月球车路径规划的多约束环境建模方法[J].国防科技大学学报,2006,28(5):106-108,118.Shi Meiping,Wu Jun,Li Yan,et al.A Multiconstrained World Modeling Method in Lunar Rover Path-planning[J].Journal of National University of Defenses Technology 2006,28(5):106-108,118.
[20]陈成,卜春光,何玉庆,等.长航程极地漫游机器人环境建模方法[J].科学通报,2013,58(增2):75-82.Chen Cheng,Bu Chunguang,He Yuqing,et al.Environment modeling for long-range polar rover robots[J].Chinese Science Bulletin,2013,58(S2):75-82.
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[22]杨健健,唐至威,王子瑞,等.基于PSO-BP神经网络的掘进机截割部故障诊断[J].煤炭科学技术,2017,45(10):129-134.Yang Jianjian,Tang Zhiwei,Wang Zirui,et al.Fault diagnosis on cutting unit of mine roadheader based on PSO-BP neural network[J].Coal Science and Technology,2017,45(10):129-134.