[1]CHENG Yi,XIAO Hongtu.Mobile-robot dynamic path planning based on improved A* and Morphin algorithms[J].CAAI Transactions on Intelligent Systems,2020,15(3):546-552.[doi:10.11992/tis.201812023]
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Mobile-robot dynamic path planning based on improved A* and Morphin algorithms

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 15 Number of periods: 2020 3 Page number: 546-552 Column: 学术论文—机器学习 Public date: 2020-05-05
Title:
Mobile-robot dynamic path planning based on improved A* and Morphin algorithms
Author(s):
CHENG Yi;  XIAO Hongtu
School of Electrical Engineering and Automation, University of Tianjin Polytechnic, Tianjin 300387, China
Keywords:
mobile robot; A* algorithm; improved A* algorithm; Morphin search tree; global-path planning; local path planning; dynamic path planning; real-time obstacle avoidanc
CLC:
TP242
DOI:
10.11992/tis.201812023
Abstract:
The traditional A* algorithm can experience collisions or path-planning failure in dynamic complicated environments. To meet global optimal requirements and achieve real-time obstacle avoidance in mobile-robot path planning, we propose a novel method that fuses an improved A* algorithm with a Morphin search tree algorithm. First, we improved the A* algorithm by reducing the selection of key nodes in the path-planning process and performing path smoothing when planning the global optimal path. Then, based on the local information obtained by the mobile-robot sensor, the Morphin search tree algorithm is used to dynamically localize the global path. Thus, obstacles are avoided both by ensuring a better global path and by real-time obstacle avoidance as the robot moves to the target. The MATLAB simulation results show that the proposed dynamic path-planning method improves both the time and path. The local path is corrected via the optimized global-path planning, dynamic obstacle avoidance, and the improved efficiency with which the robot reaches the target point.
References:
[1] QURESHI A H, AYAZ Y. Potential functions based sampling heuristic for optimal path planning[J]. Autonomous robots, 2016, 40(6): 1079-1093.
[2] SONG Baoye, WANG Zidong, ZOU Lei. On global smooth path planning for mobile robots using a novel multimodal delayed PSO algorithm[J]. Cognitive computation, 2017, 9(1): 5-17.
[3] LEE J. Heterogeneous-ants-based path planner for global path planning of mobile robot applications[J]. International journal of control, automation and systems, 2017, 15(4): 1754-1769.
[4] 李元, 王石荣, 于宁波. 基于RGB-D信息的移动机器人SLAM和路径规划方法研究与实现[J]. 智能系统学报, 2018, 13(3): 445-451
LI Yuan, WANG Shirong, YU Ningbo. RGB-D-based SLAM and path planning for mobile robots[J]. CAAI transactions on intelligent systems, 2018, 13(3): 445-451
[5] FAZLOLLAHTABAR H, HASSANLI S. Hybrid cost and time path planning for multiple autonomous guided vehicles[J]. Applied intelligence, 2017, 48(2): 482-498.
[6] HAN J, SEO Y. Mobile robot path planning with surrounding point set and path improvement[J]. Applied soft computing, 2017, 57: 35-47.
[7] SUDHAKARA P, GANAPATHY V. PRIYADHARSHINI B, et al Obstacle avoidance and navigation planning of a wheeled mobile robot using amended artificial potential field method[J]. Procedia computer science, 2018, 133: 998-1004.
[8] TAHIR Z, QURESHI A H, AYAZ Y, et al. Potentially guided bidirectionalized RRT* for fast optimal path planning in cluttered environments[J]. Robotics and autonomous systems, 2018, 108: 13-27.
[9] 朱大奇, 孙兵, 李利. 基于生物启发模型的AUV三维自主路径规划与安全避障算法[J]. 控制与决策, 2015, 30(5): 798-806
ZHU Daqi, SUN Bing, LI Li. Algorithm for AUV’s 3-D path planning and safe obstacle avoidance based on biological inspired model[J]. Control and decision, 2015, 30(5): 798-806
[10] 伍永健, 陈跃东, 陈孟元. 改进QPSO和Morphin算法下移动机器人混合路径规划[J]. 电子测量与仪器学报, 2017, 31(2): 295-301
WU Yongjian, CHEN Yuedong, CHEN Mengyuan. Hybrid path planning of mobile robot based on improved QPSO and Morphin algorithm[J]. Journal of electronic measurement and instrumentation, 2017, 31(2): 295-301
[11] MAOUDJ A, HENTOUT A, BOUZOUIA B, et al. On-line fault-tolerant fuzzy-based path planning and obstacles avoidance approach for manipulator robots[J]. International journal of uncertainty, fuzziness and knowledge-based systems, 2018, 26(5): 809-838.
[12] 万晓凤, 胡伟, 郑博嘉, 等. 基于改进蚁群算法与Morphin算法的机器人路径规划方法[J]. 科技导报, 2015, 33(3): 84-89
WAN Xiaofeng, HU Wei, ZHENG Bojia, et al. Robot path planning method based on improved ant colony algorithm and Morphin algorithm[J]. Science & technology review, 2015, 33(3): 84-89
[13] 秦玉鑫, 王红旗, 杜翠杰. 基于双层A*算法的移动机器人路径规划[J]. 制造业自动化, 2014, 36(24): 21-25, 40
QIN Yuxin, WANG Hongqi, DU Cuijie. A path planning approach to moving robot based on double layer A* Algorithm[J]. Manufacturing automation, 2014, 36(24): 21-25, 40
[14] XU Yaru, LIU Rong. Path planning for mobile articulated robots based on the improved A* algorithm[J]. International journal of advanced robotic systems, 2017, 14(4): 1-10.
[15] ZHANG Hongmei, LI Minglong. Rapid path planning algorithm for mobile robot in dynamic environment[J]. Advances in mechanical engineering, 2017, 9(12): 1-12.
[16] 王红卫, 马勇, 谢勇, 等. 基于平滑A*算法的移动机器人路径规划[J]. 同济大学学报(自然科学版), 2010, 38(11): 1647-1650
WANG Hongwei, MA Yong, XIE Yong, et al. Mobile robot optimal path planning based on smoothing A* algorithm[J]. Journal of Tongji University (Natural Science), 2010, 38(11): 1647-1650
[17] SIMMONS R, KROTKOV E, CHRISMAN L, et al. Experience with rover navigation for lunar-like terrains [C]//Proceedings of 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots. Pittsburgh, USA, 1995: 441-446.
[18] 张飞, 白伟, 乔耀华, 等. 基于改进D*算法的无人机室内路径规划[J]. 智能系统学报, 2019, 14(4): 662-669
ZHANG Fei, BAI Wei, QIAO Yaohua, et al. UAV indoor path planning based on improved D* algorithm[J]. CAAI transactions on intelligent systems, 2019, 14(4): 662-669
[19] BELGHITH K, KABANZA F, HARTMAN L. Randomized path planning with preferences in highly complex dynamic environments[J]. Robotica, 2013, 31(8): 1195-1208.
[20] 诸葛程晨, 唐振民, 石朝侠. 基于多层Morphin搜索树的UGV局部路径规划算法[J]. 机器人, 2014, 36(4): 491-497
ZHUGE Chengchen, TANG Zhenmin, SHI Zhaoxia. A local path planning algorithm for UGV based on multilayer Morphin search tree[J]. Robot, 2014, 36(4): 491-497
[21] 曹清云, 倪建军, 王康, 等. 一种改进的未知动态环境下机器人混合路径规划方法[J]. 计算机与现代化, 2016(4): 54-58
CAO Qingyun, NI Jianjun, WANG Kang, et al. A robot hybrid path planning algorithm under improved unknown and dynamic environment[J]. Computer and modernization, 2016(4): 54-58
[22] 张兆宁, 魏中慧. 危险天气下基于多重Morphin算法的终端区三维实时改航方法[J]. 南京航空航天大学学报, 2015, 47(4): 467-473
ZHANG Zhaoning, WEI Zhonghui. 3-D real-time deviation method for avoiding hazardous weather in terminal airspace based on Morphin planning algorithm[J]. Journal of Nanjing University of Aeronautics and Astronautics, 2015, 47(4): 467-473
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