基于空间位置不确定性约束的改进闭环检测算法

doi:10.13973/j.cnki.robot.2016.0301

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李维鹏, 张国良, 姚二亮, 徐君. 基于空间位置不确定性约束的改进闭环检测算法[J]. 机器人, 2016, 38(3): 301-310,321.DOI: 10.13973/j.cnki.robot.2016.0301. LI Weipeng, ZHANG Guoliang, YAO Erliang, XU Jun. An Improved Loop Closure Detection Algorithm Based onthe Constraint from Space Position Uncertainty. ROBOT, 2016, 38(3): 301-310,321. DOI: 10.13973/j.cnki.robot.2016.0301.

摘要针对在多歧义场景下移动机器人 VSLAM（visual simultaneous localization and mapping）的闭环检测问题，提出了一种基于空间位置不确定性约束的改进闭环检测算法．首先针对 ICP（迭代最近点）算法点云配准环节提出新的距离函数，弥补了欧氏距离与马氏距离的不足．其次，基于特征点的空间位置不确定性，建立视觉里程计累积误差模型并采用卡尔曼滤波减小误差．然后，根据视觉里程计累积误差模型给出闭环检测的空间范围约束．最后，根据闭环检测结果修正累积误差，进一步缩小闭环检测范围．一方面，改进算法限制了闭环检测的范围，提高了实时性；另一方面，空间约束有效排除了大部分的感知歧义，提高了闭环检测的准确率．数据集和实际场景下的对比实验均表明，对于感知歧义场景，本文提出的闭环检测算法在保证一定的召回率下，准确率明显高于 IAB-MAP、FAB-MAP 和 RTAB-MAP，并且表现出良好的实时性；对于复杂室内场景，本文算法也有着较好的实时性和准确率．

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关键词 ：同时定位与地图创建, 闭环检测, 空间位置约束, 卡尔曼滤波, 感知歧义

Abstract：An improved loop closure detection algorithm based on constraint of space position uncertainty is proposed for the loop closure detection problem in visual simultaneous localization and mapping (VSLAM) of mobile robots in perceptual aliasing scene. First of all, a new distance function is put forward for ICP (iterative closest point) algorithm to cover the shortages of Euclid distance and Mahalanobis distance in point cloud registration. Then a cumulative error model of visual odometry is established based on the space position uncertainty of feature points, and the error is decreased by Kalman filter. Next, a space range constraint for loop closure detection is given by the cumulative error model of visual odometry. Finally, the cumulative error is corrected according to the results of loop closure detection, thus the range of loop closure detection is reduced. On one hand, the improved loop closure detection algorithm proposed is of better real-time performance as a result of the range limit in loop closure detection. On the other hand, the precision ratio of loop closure detection is enhanced because most perceptual aliasing scenes are eliminated by the spatial limit. Both of the contrast experiments based on the datasets and the actual scene show that, in perceptual aliasing scenes, the improved loop closure detection algorithm proposed has a better precision ratio in a condition of high recall when compared with IAB-MAP, FAB-MAP and RTAB-MAP, and has a good real-time performance as well. In a complicated scene indoors, it also obtains good real-time performance and high accuracy.

Key words： simultaneous localization and mapping loop closure detection space position limit Kalman filter perceptual aliasing

收稿日期: 2016-01-10 录用日期: 2016-04-22

ZTFLH:

TP242

通讯作者: 李维鹏，248636779@163.com E-mail: 248636779@163.com

作者简介: 李维鹏（1992-），男，硕士生．研究领域：移动机器人VSLAM．
张国良（1970-），男，博士，教授．研究领域：智能机器人，先进控制理论与应用，组合导航．
姚二亮（1991-），男，博士生．研究领域：移动机器人SLAM．

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https://robot.sia.cn/CN/10.13973/j.cnki.robot.2016.0301 或 https://robot.sia.cn/CN/Y2016/V38/I3/301

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