参考文献/References:
[1] 周毅. 基于遗传算法的移动机器人路径规划研究[D].保定: 河北工业大学,2015.
[2]侯占军. 移动机器人自主避障方法的研究[D]. 北京:北京工业大学,2008.
[3]TANG B,ZHU Z,LUO J. Hybridizing particle swarm optimization and differential evolution for the mobile robot global path planning[J]. International journal of advanced robotic systems,2016,13(3):1-2.
[4]孙波,陈卫东,席裕庚. 基于粒子群优化算法的移动机器人全局路径规划[J]. 控制与决策,2005,20(9):1 052-1 055.
[5]陈智. 基于栅格法多目标路径规划研究[D]. 武汉:华中科技大学,2015.
[6]QU H,XING K,ALEXANDER T. An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots[J]. Neurocomputing,2013,120(10):509-517.
[7]吴青松. 基于遗传算法的移动机器人路径规划研究[D]. 成都:电子科技大学,2005.
[8]张勇,巩敦卫,任永强,等. 用于约束优化的简洁多目标微粒群优化算法[J]. 电子学报,2011,39(6):1 436-1 440.
[9]张勇. 区间多目标优化问题的微粒群优化理论及应用[D]. 徐州:中国矿业大学,2009.
[10]申晓宁,郭毓,陈庆伟,等. 多目标遗传算法在机器人路径规划中的应用[J]. 南京理工大学学报(自然科学版),2006,30(6):659-663.
[11]公茂果,焦李成,杨咚咚,等. 进化多目标优化算法研究[J]. 软件学报,2009,20(2):271-289.
[12]王明昭,王宇平,王晓丽,等. 一种均匀聚集距离的改进NSGA-Ⅱ算法[J]. 西安电子科技大学学报(自然科学版),2016,43(3):49-54.
[13]DEB K,AGRAWAL S,PRATAP A,et al. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization:NSGA-Ⅱ[J]. Lecture notes in computer science,2002,1917:849-858.
[14]陈婕,熊盛武,林婉如,等. NSGA-Ⅱ算法的改进策略研究[J]. 计算机工程与应用,2011,47(19):42-45.
[15]AHMED F,DEB K. Multi-objective optimal path planning using elitist non-dominated sorting genetic algorithms[J]. Soft computing,2013,17(7):1283-1299,.
[16]DEB K,JAIN H. An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach,part ii:handling constraints and extending to an adaptive approach[J]. IEEE transactions on evolutionary computation,2014,18(4):602-622.
相似文献/References:
[1]屈正庚,杨 川.基于改进蚁群算法的移动机器人全局轨迹规划研究[J].南京师范大学学报(自然科学版),2015,38(01):81.
Qu Zhenggeng,Yang Chuan.Research on Global Path Planning for Mobile Robot Based onImproved Ant Colony Optimization Algorithm[J].Journal of Nanjing Normal University(Natural Science Edition),2015,38(03):81.
[2]陈祥章.基于单目视觉的机器人人工势场法路径规划研究[J].南京师范大学学报(自然科学版),2014,37(01):61.
Chen Xiangzhang.Study on Artificial Potential Field Path Planning of Robot Based on Monocular Vision[J].Journal of Nanjing Normal University(Natural Science Edition),2014,37(03):61.