符号 | 符号含义 | 符号 | 符号含义 |
${\rm{obs}}$ | 障碍物 | ${\bf{X}}{\rm{d}}$ | 目标位置 |
${U_{{\rm{Xd}}}}(x)$ | 引力势能 | ${U_{{\rm{obs}}}}(x)$ | 斥力势能 |
${U_{{\rm{art}}}}(x)$ | 总势能 | ${{F}}$ | 合力 |
${{{F}}_{{\rm{Xd}}}}$ | 吸引力 | ${{F}}_{\rm{obs}}$ | 排斥力 |
$j$ | 移动机器人感知到的周边障碍物的个数 |

Citation: Qinghua LI, Yue YOU, Yaqi MU, Zhao ZHANG, Chao FENG. Integrated Navigation Algorithm for Large Concave Obstacles[J]. Journal of Electronics and Information Technology, doi: 10.11999/JEIT190179

一种针对大型凹型障碍物的组合导航算法
English
Integrated Navigation Algorithm for Large Concave Obstacles
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[1]
王勇臻, 陈燕, 于莹莹. 求解多旅行商问题的改进分组遗传算法[J]. 电子与信息学报, 2017, 39(1): 198–205. doi: 10.11999/JEIT160211
WANG Yongzhen, CHEN Yan, and YU Yingying. Improved grouping genetic algorithm for solving multiple traveling salesman problem[J]. Journal of Electronics &Information Technology, 2017, 39(1): 198–205. doi: 10.11999/JEIT160211 -
[2]
黄长强, 赵克新. 基于改进蚁狮算法的无人机三维航迹规划[J]. 电子与信息学报, 2018, 40(7): 1532–1538. doi: 10.11999/JEIT170961
HUANG Changqiang and ZHAO Kexin. Three dimensional path planning of UAV with improved ant lion optimizer[J]. Journal of Electronics &Information Technology, 2018, 40(7): 1532–1538. doi: 10.11999/JEIT170961 -
[3]
KHATIB O. Real-time obstacle avoidance for manipulators and mobile robots[J]. The International Journal of Robotics Research, 1986, 5(1): 90–98. doi: 10.1177/027836498600500106
-
[4]
PARK M G, JEON J H, and LEE M C. Obstacle avoidance for mobile robots using artificial potential field approach with simulated annealing[C]. 2001 IEEE International Symposium on Industrial Electronics, Pusan, South Korea, 2001: 1530–1535. doi: 10.1109/ISIE.2001.931933.
-
[5]
况菲, 王耀南. 基于混合人工势场-遗传算法的移动机器人路径规划仿真研究[J]. 系统仿真学报, 2006, 18(3): 774–777. doi: 10.16182/j.cnki.joss.2006.03.061
KUANG Fei and WANG Yaonan. Robot path planning based on hybrid artificial potential field/genetic algorithm[J]. Journal of System Simulation, 2006, 18(3): 774–777. doi: 10.16182/j.cnki.joss.2006.03.061 -
[6]
LEE D, JEONG J, KIM Y H, et al. An improved artificial potential field method with a new point of attractive force for a mobile robot[C]. The 2017 2nd International Conference on Robotics and Automation Engineering, Shanghai, China, 2017: 63–67. doi: 10.1109/ICRAE.2017.8291354.
-
[7]
ROSTAMI S M H, SANGAIAH A K, WANG Jin, et al. Obstacle avoidance of mobile robots using modified artificial potential field algorithm[J]. EURASIP Journal on Wireless Communications and Networking, 2019, 2019(1): 70. doi: 10.1186/s13638-019-1396-2
-
[8]
HART P E, NILSSON N J, and RAPHAEL B. A formal basis for the heuristic determination of minimum cost paths[J]. IEEE Transactions on Systems Science and Cybernetics, 1968, 4(2): 100–107. doi: 10.1109/TSSC.1968.300136
-
[9]
DECHTER R and PEARL J. Generalized best-first search strategies and the optimality of A*[J]. Journal of the ACM, 1985, 32(3): 505–536. doi: 10.1145/3828.3830
-
[10]
田景文, 孔垂超, 高美娟. 一种车辆路径规划的改进混合算法[J]. 计算机工程与应用, 2014, 50(14): 58–63. doi: 10.3778/j.issn.1002-8331.1208-0319
TIAN Jingwen, KONG Chuichao, and GAO Meijuan. Improved hybrid algorithm of vehicle path planning[J]. Computer Engineering and Applications, 2014, 50(14): 58–63. doi: 10.3778/j.issn.1002-8331.1208-0319 -
[11]
胡中华, 潘洲, 王凯凯. 基于混合算法的动态路径规划[J]. 煤矿机械, 2015, 36(12): 243–245. doi: 10.13436/j.mkjx.201512103
HU Zhonghua, PAN Zhou, and WANG Kaikai. Dynamic path planning based on hybrid algorithm[J]. Coal Mine Machinery, 2015, 36(12): 243–245. doi: 10.13436/j.mkjx.201512103 -
[12]
唐志荣, 冀杰, 吴明阳, 等. 基于改进人工势场法的车辆路径规划与跟踪[J]. 西南大学学报: 自然科学版, 2018, 40(6): 174–182. doi: 10.13718/j.cnki.xdzk.2018.06.025
TANG Zhirong, JI Jie, WU Mingyang, et al. Vehicles path planning and tracking based on an improved artificial potential field method[J]. Journal of Southwest University:Natural Science Edition, 2018, 40(6): 174–182. doi: 10.13718/j.cnki.xdzk.2018.06.025 -
[13]
赵奇, 赵阿群. 一种基于A*算法的多径寻由算法[J]. 电子与信息学报, 2013, 35(4): 952–957. doi: 10.3724/SP.J.1146.2012.00983
ZHAO Qi and ZHAO Aqun. A multi-path routing algorithm base on A* algorithm[J]. Journal of Electronics &Information Technology, 2013, 35(4): 952–957. doi: 10.3724/SP.J.1146.2012.00983 -
[14]
DIJKSTRA E W. A note on two problems in connexion with graphs[J]. Numerische Mathematik, 1959, 1(1): 269–271. doi: 10.1007/BF01386390
-
[15]
沈文君. 基于改进人工势场法的机器人路径规划算法研究[D]. [硕士论文], 暨南大学, 2009.
SHEN Wenjun. Algorithm research of path planning for robot based on improved artifical potential field[D]. [Master dissertation], Jinan University, 2009.
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表 1 人工势场法符号含义
表 2 A*算法符号含义
符号 符号含义 符号 符号含义 $g(\cdot )$ 从初始节点到当前移动机器人所在节点node的
启发式评估代价$h(\cdot )$ 从当前移动机器人所在节点node到目标节点的
启发式评估代价$(x_{\rm{start}},y_{\rm{start}})$ 初始节点坐标 $(x_{\rm{goal}},y_{\rm{goal}})$ 目标节点坐标 $(x,y)$ 移动机器人实时位置坐标 表 3 模型描述符号含义
符号 符号含义 符号 符号含义 $O_1$ 障碍物的左端点 $O_2$ 障碍物的右端点 $2\alpha $ 障碍物的长 $\beta $ 障碍物的宽 $v_t$ 移动机器人的实时线速度 $a$ 移动机器人在运行态时的最大速度 $\Delta d$ 移动机器人在某段时间内的移动距离 $S_{\rm{obs}}$ 所有障碍物总面积 $S_{\rm{map}}$ 地图面积 $\rho $ 障碍物密度 表 4 算法性能比较
算法 时间(s) 路径长度(m) A*算法 22.40 1040.69 改进人工势场法[15] 无穷大 无穷大 本文组合算法 10.62 707.09 -