[1]蒲兴成,赵红全,张毅.细菌趋化行为的移动机器人路径规划[J].智能系统学报,2014,9(01):69-75.[doi:10.3969/j.issn.1673-4785.201305050]
 PU Xingcheng,ZHAO Hongquan,ZHANG Yi.Mobile robot path planning research based on bacterial chemotaxis[J].CAAI Transactions on Intelligent Systems,2014,9(01):69-75.[doi:10.3969/j.issn.1673-4785.201305050]
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细菌趋化行为的移动机器人路径规划(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年01期
页码:
69-75
栏目:
学术论文—智能系统
出版日期:
2014-02-25

文章信息/Info

Title:
Mobile robot path planning research based on bacterial chemotaxis
作者:
蒲兴成12 赵红全2 张毅2
1. 重庆邮电大学 数理学院, 重庆 400065;
2. 重庆邮电大学 自动化学院, 重庆 400065
Author(s):
PU Xingcheng12 ZHAO Hongquan2 ZHANG Yi2
1. School of Mathematics and Physics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China;
2. School of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
关键词:
机器人细菌趋化高斯势场环境避障路径规划
Keywords:
robotbacterial chemotaxisGaussian potential environment modelobstacle avoidancepath planning
分类号:
TP24
DOI:
10.3969/j.issn.1673-4785.201305050
摘要:
针对移动机器人路径规划问题, 结合细菌觅食趋化过程的相似性, 提出了一种类似细菌趋化行为的移动机器人路径规划方法。该方法模拟细菌的觅食环境, 为机器人建立类似的障碍物轮廓和目标轮廓模型, 通过设置一定的趋向和避障权重, 并结合智能机器人的自身传感器技术, 为机器人在简单甚至复杂的环境下提供相应的路径运动策略, 达到实现实时导航任务的目的。在高斯势场环境下进行仿真实验, 与Sierakowski的方法进行比较, 实验结果表明该方法获取的路径具有更好的安全性、实时性和平滑性, 说明了所提方法不仅能实现机器人的路径规划任务, 而且规划的路径能使机器人在障碍物密集的区域内灵活调整位姿。
Abstract:
In order to solve the problem of mobile robot path planning, this paper puts forward a method of mobile robot path planning based on bacterial chemotaxis. Simulating the bacterial foraging environment, this method builds similar obstacle contours and the target contour models. Through setting some tendency and obstacle weight and combining intelligent robot sensing technology, it can offer relative sports strategy for mobile robots under simple or even complex environments and thus utilizes real-time navigation. By using this method in the Gaussian potential environment, the robot can not only find its path, but it can also adjust its position and attitude under complicated environments as compared with the Sierakowski method, and the experimental results show that this method can get a better path with security, real-time performance and flatness.

参考文献/References:

[1] TSUJI T, SUZUKI M, TAKIGUCHI M, et al. Biomimetic control based on a model of chemotaxis in escherichia coli[J]. Artificial Life, 2010, 16(2): 155-177.
[2] PASSINO K M. Biomimicry of bacterial foraging for distributed optimization and control[J]. IEEE Control System Magazine, 2002, 22(3): 52-67.
[3] PASSINO K M. Bacterial foraging optimization[J]. International Journal of Swarm Intelligence Research, 2010, 1(1): 1-16.
[4] 周雅兰.细菌觅食优化算法的研究与应用[J].计算机工程与应用, 2010, 46(20): 16-21.ZHOU Yalan. Research and application on bacterial foraging optimization algorithm[J]. Computer Engineering and Applications, 2010, 46(20): 16-21.
[5] BREMERMANN H J. Chemotaxis and optimization[J]. Journal of The Franklin Institute, 1974, 297(5): 397-404.
[6] MULLER S D, AIRAGHI J, MARCHETTO S, et al. Optimization based on bacterial chemotaxis[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(1): 16-29.
[7] DHARIWAL A, SUKHATME G, REQUICHA A G. Bacterium-inspired robots for environmental monitorng[C]//Proceedings of the 2006 IEEE International Conference on Robotics and Automation. New Orleans, USA, 2004: 1436-1443.
[8] COELHO L D S, SIERAKOWSKI C A. Bacteria colony approaches with variable velocity applied to path optimization of mobile robots[C]//ABCM Symposium Series in Mechatronics. Rio de Janeiro, Brazil: ABCM, 2006, 2: 297-304.
[9] SIERAKOWSKI C A, COELHO L S. Study of two swarm intelligence techniques for path planning of mobile robots[C]//Proceedings of the 16th IFAC World Congress. Prague, Czech Republic, 2005: 1-6.
[10] SIERAKOWSKI C A, COELHO L S. Path planning optimization for mobile robots based on bacteria colony approach[J]. Advances in Soft Computing, 2006, 34: 187-198.
[11] 蒲兴成,张军,张毅.基于时变适应度函数的改进粒子群算法及其在移动机器人路径规划中的应用[J].计算机应用研究, 2011, 27(12): 4454-4456, 4463.PU Xingcheng, ZHANG Jun, ZHANG Yi. Path planning method for mobile robot based on particle swarm optimization with time-varying fitness function[J]. Application Research of Computers, 2010, 27(12): 4454-4456, 4463.
[12] 蒲兴成,赵红全,张毅.基于改进细菌趋化步长的移动机器人路径规划方法研究[J].山东科技大学学报:自然科学版, 2012, 31(4): 56-62.PU Xingcheng, ZHAO Hongquan, ZHANG Yi. Mobile robot path planning based on bacterial chemotaxis step[J]. Journal of Shandong University of Science and Technology: Natural Science, 2012, 31(4): 56-62.

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备注/Memo

备注/Memo:
收稿日期:2013-05-15。
基金项目:国家自然科学基金资助项目(60905066);科技部国际合作项目(2010DFA12160);重庆市科技攻关计划资助项目(CSTC2010AA2055).
作者简介:赵红全,男,1987年生,硕士研究生,主要研究方向为智能算法与机器人控制;张毅,男,1966年生,教授,博士生导师,中国人工智能学会理事、青年工作委员会副主任、智能机器人专业委员会委员,中国计量测试学会高级会员,《机器人技术及其应用》杂志理事。主要研究方向为智能服务机器人、信息无障碍技术、智能人机交互技术。申请国家专利20余项,获得国家发明专利10余项,发表学术论文150余篇,其中被SCI、EI、ISTP检索80余篇,出版专著2部,撰写教材4部。
通讯作者:蒲兴成,男,1973年生,副教授,博士,主要研究方向为非线性控制、随机系统和智能控制等。主持和参与省部级基金项目8项,发表学术论文40余篇,出版专著1部、教材1部.E-mail:puxc@cqupt.edu.cn.
更新日期/Last Update: 1900-01-01