[1]马健,俞扬.一种基于全局位置估计误差的路标探索策略[J].智能系统学报,2014,9(3):313-318.[doi:10.3969/j.issn.1673-4785.201310014]
MA Jian,YU Yang.Landmark exploration strategy using estimated global localization error[J].CAAI Transactions on Intelligent Systems,2014,9(3):313-318.[doi:10.3969/j.issn.1673-4785.201310014]
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MA Jian,YU Yang.Landmark exploration strategy using estimated global localization error[J].CAAI Transactions on Intelligent Systems,2014,9(3):313-318.[doi:10.3969/j.issn.1673-4785.201310014]
一种基于全局位置估计误差的路标探索策略
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
9
期数:
2014年第3期
页码:
313-318
栏目:
学术论文—智能系统
出版日期:
2014-06-25
- Title:
- Landmark exploration strategy using estimated global localization error
- Keywords:
- SLAM; landmark discovery; Kalman filter; path planning; global error
- 分类号:
- TP181
- 摘要:
- 自主移动机器人在未知环境中探索和估计路标的方法主要基于SLAM技术。提出一种以全局定位误差最小化为指导的基于SLAM的探索策略。以全局定位误差的估计为准则, 采用Monte Carlo采样来贪心地优化每一步的行走路径。考虑到SLAM估计的惯性, 文中对较大转弯角度进行惩罚, 使机器人更倾向于平滑的行走轨迹, 从而进一步提高路标位置的估计精度。文中还将全局定位信息引入SLAM的机器人自身位置估计中, 由于全局定位信息历史运动轨迹, 该方法能够有效地校正当机器人移动变化过大时SLAM估计的误差。实验显示了文中方法的有效性。
- Abstract:
- Exploration and estimation of landmarks in an unknown environment is an important skill for autonomous robots, most of which are based on the SLAM technique. This paper presents an SLAM based exploration strategy to minimize the global localization error, via greedily optimizing every step by Monte Carlo sampling. Due to the inertia of the SLAM method, we then penalize a large change of direction for a smoother trajectory, which may result in a more accurate estimation of landmarks. To further calibrate the estimation error for a large range of movement, the global localization information is introduced to the procedure of the estimation of the robot, since it depends less on the historical movement trajectory. Experiments verified the effectiveness of the proposed method.
- 参考文献/References:
-
[1] DURRANT-WHYTE H F. An autonomous guided vehicle for cargo handling applications[J]. International Journal of Robotics Research, 1996, 15(5):407-440.
[2] MONTEMERLO M, PINEAU J, ROY N, et al. Experiences with a mobile robotic guide for the elderly[C]//Proceedings of the 18th National Conference on Artificial Intelligence. Edmonton, Canada. 2002:587-592.
[3] HUNTSBERGER T, AGHAZARIAN H, CHENG Y, et al. Rover autonomy for long range navigation and science data acquisition on planetary surfaces[C]//Proceedings of IEEE International Conference on Robotics and Automation. Washington, DC, 2002:3161-3168.
[4] SMITH R, SELF M, Cheeseman P. Estimating uncertain spatial relationships in robotics[M]. Autonomous Robot Vehicles, 1990:167-193.
[5] LI C, HUANG Y, KANG Y, et al. Monocular SLAM using vertical straight lines with inverse-depth representation[C]//Proceedings of 7th IEEE World Congress on Intelligent Control and Automation. Chongqing, China, 2008:3015-3020.
[6] THRUN S, BURGARD W, FOX D. A probabilistic approach to concurrent mapping and localization for mobile robots[J]. Autonomous Robots, 1998, 5(3/4):253-271.
[7] GRISETTI G, STACHNISS C, BURGARD W. Improved techniques for grid mapping with Rao-Blackwellized particle filters[J]. IEEE Transactions on Robotics, 2007, 23(1):34-46.
[8] 张恒, 樊晓平. 移动机器人同步定位与地图构建过程中的轨迹规划研究[J]. 机器人, 2006, 28(3):285-290.ZHANG Heng, FAN Xiaoping. Mobile robot trajectory planning in simultaneous localization and mapping problem[J]. Robot, 2006, 28(3):285-290.
[9] NEWMAN P. On the structure and solution of the simultaneous localisation and map building problem[D]. Sydney:University of Sydney, 1999:1-5.
[10] 熊蓉. 室内未知环境线段特征地图构建[D]. 杭州:浙江大学, 2009:10-23.XIONG Rong.Line feature map building for unknown indoor environments[D].Hangzhou:Zhejiang University, 2009:10-23.
[11] DISSANAYAKE M W M G, NEWMAN P, CLARK S, et al. A solution to the simultaneous localization and map building (SLAM) problem[J]. IEEE Transactions on Robotics and Automation, 2001, 17(3):229-241.
[12] CASTELLANOS J A, MONTIEL J M M, NEIRA J, et al. The SPmap:A probabilistic framework for simultaneous localization and map building[J]. IEEE Transactions on Robotics and Automation, 1999, 15(5):948-952.
[13] WILLIAMS S, DISSANAYAKE G, DURRANT-WHYTE H F. Towards terrain-aided navigation for underwater robotics[J]. Advanced Robotics, 2001, 15(5):533-549.
[14] THRUN S. Probabilistic algorithms in robotics[J]. AI Magazine, 2000, 21(4):93-109.
[15] HAHNEL D, BURGARD W, FOX D, et al. An efficient FastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements[C]//Proceedings of 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems. Las Vegas, NV, 2003:206-211.
[16] 李一波, 张庆涛. 室内未知环境遍历路径规划算法综述[J]. 计算机科学, 2012, 39(11A):334-338.LI Yibo, ZHANG Qingtao.Review of coverage path planning arithmetic in unknown indoor environment[J].Computer Science, 2012, 39(11A):334-338.
[17] ULRICH I, MONDADA F, NICOUD J D. Autonomous vacuum cleaner[J]. Robotics and Autonomous Systems, 1997, 19(3):233-245.
[18] OH J S, PARK J B, CHOI Y H. Complete coverage navigation of clean robot based on triangular cell map[J]. IEEE Transactions on Industrial Electronics, 2004, 51(3):718-726.
[19] JEBARI I, BAZEILLE S, FILLIAT D. Informatics in control, automation and robotics[M]. Berlin:Springer, 2012:224-237.
- 相似文献/References:
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[1]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.[doi:10.11992/tis.201702005]
LI Yuan,WANG Shirong,YU Ningbo.RGB-D-based SLAM and path planning for mobile robots[J].CAAI Transactions on Intelligent Systems,2018,13():445.[doi:10.11992/tis.201702005]
备注/Memo
收稿日期:2014-03-25。
基金项目:国家自然科学基金面上项目资助项目(61375061);江苏省自然科学基金青年基金资助项目(BK2012303)
作者简介:马健,1990年生,男,硕士研究生,主要研究方向为演化计算、强化学习。
通讯作者:俞扬,1982年生,男,助理研究员,博士,主要研究方向为人工智能、机器学习、演化计算、强化学习,发表学术论文20余篇,yuy@lamda.nju.edu.cn。
更新日期/Last Update:
1900-01-01