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基于新型人工路标系统的移动机器人视觉SLAM方法研究
Alternative TitleResearch on Visual SLAM Method Based on a Novel Artificial Landmark System for Mobile Robot
温丰
Subtype工学博士
Thesis Advisor原魁
2010-05-30
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword同时定位与地图构建 移动机器人 人工路标 视觉导航 Mr二维码 多传感器信息融合 Simultaneous Localization And Mapping Mobile Robot Artificial Landmark Visual Navigation Mr Code Multi-sensor Information Fusion
Abstract机器人同时定位与地图构建(SLAM)是实现真正意义上的全自主移动机器人的关键。路标的特征化、数据关联、计算开销等各方面对于一个实用的SLAM算法都至关重要。一方面,视觉传感器可以提供对象形状、颜色、纹理等丰富信息,据此便于形成稳定的数据关联,有助于SLAM中运动闭环的判断。另一方面,在现有的研究水平和技术条件下,合理设计人工路标是在复杂环境中准确、快速完成SLAM的有效手段。鉴于此,本文在国家自然科学基金的资助下,对基于新型人工路标系统的室内移动机器人视觉SLAM方法进行了探讨和研究,主要工作和创新之处包括: 第一,针对MR二维码在机器人快速运动时易出现误识别问题,提出了一种改进的MR二维码识别算法,该方法提高了识别的准确率,有助于SLAM中的数据关联等问题的解决。 第二,在对机器人运动模型和视觉传感器观测模型进行分析和验证的基础上,给出一种实用的里程计位置估计误差模型,提出了基于混合数据关联的扩展卡尔曼滤波(EKF)SLAM方法,实验结果表明该算法可提高机器人定位和构建地图的精度,验证了算法的有效性、鲁棒性和一致性。 第三,提出了一种改进的带多重次优渐消因子 的强跟踪滤波(EMF-STF)SLAM算法,并针对SLAM问题中路标观测不连续的情况给出了 的计算方法。该算法不但可降低线性化过程所引入的误差,提高定位以及构建地图精度,并且能够将协方差抑制在一个较小的范围内,从而提高构建地图的可信度。 第四,利用MR二维码,结合趋近控制算法和改进的循线算法,给出并实现了一种适用于室内移动机器人的已知环境地图情况下的实用拓扑导航策略,并在实际实验中验证了该策略的合理性和有效性。 最后,基于以上工作,完成了一套基于MR二维码的机器人视觉SLAM与导航实验系统,设计开发了具有友好交互界面的实验软件SLAM-NAV。借助于该系统,机器人可灵活方便地在室内环境中完成地图构建和自主导航,从而验证了本文所提方法和策略的实用性和有效性。
Other AbstractSimultaneous Localization and Mapping (SLAM) is the key to implementing truly autonomous mobile robots. Landmark characterization, data association and computational complexity are vital in achieving a practical SLAM implementation. On the one hand, vision sensors can provide rich information about shape, color and texture, which is useful to form reliable data association and predict a closing loop; on the other hand, under the present research level and technical conditions, rational design of artificial landmarks is an effective means for implementing SLAM in a complex environment. In view of this, supported by the National Natural Scientific Foundation, this thesis has studied on the visual SLAM method based on a novel artificial landmark system. The novel work and contributions of this thesis includes: Firstly, an improved recognition algorithm is proposed for the false recognition problem during the rapid movement of the robot, which improves the recognition accuracy and contributes to solution of the data association problem in SLAM. Secondly, a practical error model for odometric position estimation is proposed on the basis of analysis and verification of the motion model and observation model. An improved extended Kalman filter (EKF) SLAM algorithm based on mixed data association is presented, which improves the localization precision of the robot and the map accuracy. Experimental results verify the effectiveness, robustness and consistency of the algorithm. Thirdly, an extended multiple fading strong tracking filter (EMF-STF) SLAM algorithm is proposed and the calculation method of the multiple fading factors is also described. The algorithm is able to decrease the error induced by the linearization, improve the localization precision and the map accuracy and constrain the covariance within a small range to enhance the credibility of the map. Fourthly, making use of the MR code, a practical topological navigation strategy is proposed for indoor mobile robots when the environment map is known, combined with an approaching control algorithm and an extended line tracking algorithm. Experimental results show the rationality and effectiveness of the strategy in the real environment. Finally, on the basis of the above work, a visual SLAM and navigation experimental system based on MR code has been implemented and an experimental software SLAM-NAV with a friendly man-machine interface has been developed. Utilizing the system, the robot can comp...
shelfnumXWLW1481
Other Identifier200718014628022
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6266
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
温丰. 基于新型人工路标系统的移动机器人视觉SLAM方法研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2010.
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