一种基于导航误差空间的无人水下航行器路径规划方法

doi:10.3969/j.issn.1000-1093.2014.08.017

兵工学报 ›› 2014, Vol. 35 ›› Issue (8): 1243-1250.doi: 10.3969/j.issn.1000-1093.2014.08.017

一种基于导航误差空间的无人水下航行器路径规划方法

严浙平，赵玉飞，陈涛，周佳加

(哈尔滨工程大学自动化学院, 黑龙江哈尔滨 150001)

收稿日期:2013-07-01 修回日期:2013-07-01 上线日期:2014-11-03
作者简介:严浙平(1972—)，男，教授，博士生导师
基金资助:
国家自然科学基金项目（51179038）；新世纪优秀人才计划项目(NCET-10-0053)

A Novel Method of UUV Path Planning Based on Navigation Error Space

YAN Zhe-ping， ZHAO Yu-fei， CHEN Tao， ZHOU Jia-jia

(College of Automation, Harbin Engineering University, Harbin 150001, Heilongjiang, China)

Received:2013-07-01 Revised:2013-07-01 Online:2014-11-03

摘要/Abstract

摘要： 无人水下航行器(UUV)的传统路径规划方法常忽略对路径安全有重要影响的导航误差约束。针对此问题，将导航误差引入环境模型中，提出一种基于导航误差空间(NES)的全局路径规划方法。NES综合自身位置、导航误差和环境信息，将随机导航误差转化为有确定代价的约束条件。提出符合实际导航特点的导航误差传递模型，并采用圆概率偏差（CEP）评估导航精度。目标代价同时考虑了路径长度和航行安全性等因素。运用改进A^*算法进行路径搜索，获得最优路径。数字海洋环境仿真实验表明，提出的规划算法简便、快速，可有效降低路径的安全风险。

关键词: 控制科学与技术, 无人水下航行器, 导航误差空间, 全局规划, 圆概率偏差

Abstract: The traditional path planning of unmanned underwater vehicle (UUV) frequently ignores the navigation errors which have significant impact on the path safety. To solve the problem, a method of global path planning based on navigation error space (NES) is proposed, which introduces the navigation error into environment model. NES is built, including position, navigation error and environmental information, which translates the stochastic navigation error into deterministic constrains. The error propagation model is applied, and CEP is used to evaluate the positioning accuracy. The path length and sail safety are considered in the objective cost function. An improved A^* based algorithm is applied for searching the optimal path. Simulation experiment of marine environment show that the proposed approach is simple and fast, and path risk is decreased efficiently.

Key words: control science and technology, unmanned underwater vehicle, navigation error space, global planning, CEP

中图分类号:

严浙平，赵玉飞，陈涛，周佳加. 一种基于导航误差空间的无人水下航行器路径规划方法[J]. 兵工学报, 2014, 35(8): 1243-1250.

YAN Zhe-ping， ZHAO Yu-fei， CHEN Tao， ZHOU Jia-jia. A Novel Method of UUV Path Planning Based on Navigation Error Space[J]. Acta Armamentarii, 2014, 35(8): 1243-1250.

参考文献

［1］李俊, 徐德民, 宋保维, 等. 自主式水下潜器导航技术现状与展望［J］. 中国造船, 2004, 45(3):70-77.
LI Jun, XU De-min, SONG Bao-wei, et al. Development and prospect of AUV navigation technology［J］. Shipbuilding of China, 2004, 45(3):70-77. (in Chinese)
［2］ Berg J V D, Patil S, Alterovitz R. Motion planning under uncertainty using iterative local optimization in belief space［J］. The International Journal of Robotics Research, 2012, 31(11):1263-1278.
［3］ Kurniawati H, Bandyopadhyay T, Patrikalakis N M. Global motion planning under uncertain motion, sensing, and environment map［J］. Auton Robot, 2012, 33:255-272.
［4］ Chakravorty S, Kumar S. Generalized sampling-based motion planners［J］. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 2011, 41(3):856-866.
［5］ Bry A, Roy N. Rapidly-exploring random belief trees for motion planning under uncertainty［C］∥IEEE International Conference on Robotics and Automation. Shanghai: IEEE, 2011: 723-730.
［6］ Du T N E，Burdick J W. Robot motion planning in dynamic, uncertain environments［J］. IEEE Transactions on Robotics, 2012, 28(1): 101-115.
［7］ González-Sieira A, Mucientes M, Bugarin A. A state lattice approach for motion planning under control and sensor uncertainty［C］∥ROBOT2013:First Iberian Robotics Conference. Madrid, Spain:Springer, 2014: 247-260.
［8］ Censi A, Calisi D, Luca A D, et al. A Bayesian framework for optimal motion planning with uncertainty［C］∥ 2008 IEEE International Conference on Robotics and Automation. Pasadena, US:IEEE, 2008:1798-1805.
［9］ Gonzalez J P. Planning with uncertainty in position using high-resolution maps［D］. Pittsburgh: Carnegie Mellon University, 2008:36-42.
［10］ Lambert A, Gruyer D. Safe path planning in an uncertain-configuration space［C］∥2003 IEEE International Conference on Robotics and Automation. Taipei:IEEE, 2003:4185-4190.
［11］冀大雄, 刘健. 水下机器人圆概率偏差的有效预报［J］.计算机应用, 2012, 32(10): 2960-2962.
JI Da-xiong, LIU Jian. Effective forecast of circular error probability in underwater robots［J］. Journal of Computer Application, 2012, 32(10): 2960-2962. (in Chinese)
［12］ Moon I, Miura J, Yoshiaki S. On-line viewpoint and motion planning for efficient visual navigation under uncertainty［J］. Robotics and Autonomous Systems, 1999, 28(2/3): 237-248.
［13］ Hagen O K, Anonsen K B, Mandt M. The HUGIN real-time terrain navigation system［C］∥Oceans 2010. Kjeller, Norway:MTS/IEEE, 2010:1-7.
［14］张红梅，赵建虎，杨鲲，等.水下导航定位技术［M］.武汉：武汉大学出版社, 2010: 1-3.
ZHANG Hong-mei, ZHAO Jian-hu, YANG Kun, et al. Underwater navigation and positioning technology［M］. Wuhan:Wuhan University Press, 2010:1-3. (in Chinese)
［15］王艳永, 贾兴荣, 高晖,等. 基于统计推断的惯性定位精度评估方法对比［J］.计算机应用, 2012, 32(增刊2):276-279.
WANG Yan-yong, JIA xing-rong, GAO Hui, et al. Comparison of inertial positioning accuracy evaluation approaches based on statistical inference［J］. Journal of Computer Applications, 2012, 32(S2):276-279. (in Chinese)
［16］ Gonzalez J P, Dornbush A, Likhachev M. Using state dominance for path planning in dynamic environments with moving obstacles［C］∥2012 IEEE International Conference on Robotics and Automation. Saint Paul, US:IEEE, 2012:4009-4015.

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一种基于导航误差空间的无人水下航行器路径规划方法

A Novel Method of UUV Path Planning Based on Navigation Error Space

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