VorSLAM算法中基于多规则的数据关联方法

郭帅; 马书根; 李斌; 王明辉; 王越超

doi:10.3724/SP.J.1004.2013.00883

VorSLAM算法中基于多规则的数据关联方法

doi: 10.3724/SP.J.1004.2013.00883

郭帅^1,2, ,,
马书根^{1 3},
李斌¹,
王明辉¹,
王越超¹

1.
中国科学院沈阳自动化研究所机器人学国家重点实验室沈阳 110016 中国;
2.
中国科学院大学北京 100049 中国;
3.
日本立命馆大学机器人系草津 525-8577 日本

基金项目:

国家自然科学基金(61075103)资助

详细信息

通讯作者:
郭帅

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- 被引次数: 0
出版历程
- 收稿日期: 2011-11-23
- 修回日期: 2012-08-27
- 刊出日期: 2013-06-20

A Data Association Approach Based on Multi-rules in VorSLAM

GUO Shuai^{1,2
, ,},
MA Shu-Gen^{1 3},
LI Bin¹,
WANG Ming-Hui¹,
WANG Yue-Chao¹

1.
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;
2.
University of Chinese Academy of Sciences, Beijing 100049, China;
3.
Department of Robotics, Ritsumeikan University, Kusatsu-Shi 525-8577, Japan

Funds:

Supported by National Natural Science Foundation of China(61075103)

摘要

摘要: 针对单独依据马氏距离(Mahalanobis distance)的数据关联(Data association, DA)算法不能保证输出正确结果的问题, 结合VorSLAM (Voronoi partition based SLAM)算法所采用的混合地图表示方法的特点, 本文提出了一个基于多规则的数据关联方法. 该数据关联方法依据的规则包括局部搜索规则、传感器观测特征的单向性规则、马氏距离规则和轮廓匹配规则,诸个规则在每个数据关联周期依次执行. 局部搜索规则和传感器观测特征的单向性规则可以有效地降低数据关联的搜索空间,同时可避免一类潜在的数据关联错误; 马氏距离利用了特征参数表示的特征位置信息寻找多个可能的数据关联假设; 根据VorSLAM算法中局部地图描述了产生对应特征的局部环境轮廓信息, 轮廓匹配规则从多个可能的数据关联假设中识别出正确的数据关联假设. 基于多规则的数据关联方法系统可靠地解决了VorSLAM算法中的数据关联问题, 方法的有效性通过两个室内环境的实验得到了验证.
- 数据关联 /
- 马氏距离 /
- 同步定位与地图创建 /
- 地图创建
Abstract: To solve the problem that the data association (DA) algorithm based only on Mahalanobis distance cannot ensure to produce correct results, this paper proposes a data association approach based on multi-rules, which has utilized the characteristic of the hybrid metric map representation, adopted in VorSLAM. This approach consists of the rule of local searching, the rule of unidirectivity existing in the corner's observation, the rule of Mahalanobis distance and the rule of shape matching. These rules execute in turn in each data association circle. The former two rules decrease the searching space of the data association and avoid a sort of wrong data association. The rule of Mahalanobis distance can produce a set of potential data association hypothese according to the location information expressed in the feature's parameters. Utilizing the characteristic that in VorSLAM each local map describes the local environment's contour of its corresponding feature, the rule of shape matching finally recognizes the correct data association hypothesis. The data association based on multi-rules has systematically and reliably solved the data association problem in VorSLAM. The efficiency of the proposed approach is verified in two experiments carried out in indoor environments.
- Data association (DA) /
- Mahalanobis distance /
- simultaneous localization and mapping (SLAM) /
- mapping

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参考文献(22)

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