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首页> 外文会议>Unmanned Systems Technology IX; Proceedings of SPIE-The International Society for Optical Engineering; vol.6561 >Precise Visual Navigation Using Multi-Stereo Vision and Landmark Matching
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Precise Visual Navigation Using Multi-Stereo Vision and Landmark Matching

机译：使用多立体视觉和地标匹配进行精确的视觉导航

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摘要

Traditional vision-based navigation system often drifts over time during navigation. In this paper, we propose a set of techniques which greatly reduce the long term drift and also improve its robustness to many failure conditions. In our approach, two pairs of stereo cameras are integrated to form a forward/backward multi stereo camera system. As a result, the Field-Of-View of the system is extended significantly to capture more natural landmarks from the scene. This helps to increase the pose estimation accuracy as well as reduce the failure situations. Secondly, a global landmark matching technique is used to recognize the previously visited locations during navigation. Using the matched landmarks, a pose correction technique is used to eliminate the accumulated navigation drift. Finally, in order to further improve the robustness of the system, measurements from low-cost Inertial Measurement Unit (IMU) and Global Positioning System (GPS) sensors are integrated with the visual odometry in an extended Kalman Filtering framework. Our system is significantly more accurate and robust than previously published techniques (1～5% localization error) over long-distance navigation both indoors and outdoors. Real world experiments on a human worn system show that the location can be estimated within 1 meter over 500 meters (around 0.1% localization error averagely) without the use of GPS information.
机译：传统的基于视觉的导航系统通常会在导航过程中随时间漂移。在本文中，我们提出了一套技术，可大大减少长期漂移并提高其在许多故障条件下的鲁棒性。在我们的方法中，将两对立体声相机集成在一起以形成一个前/后多立体声相机系统。结果，系统的视野得到了显着扩展，可以从场景中捕获更多自然的地标。这有助于提高姿态估计的准确性，并减少故障情况。其次，全球地标匹配技术用于在导航期间识别先前访问的位置。使用匹配的地标，使用姿势校正技术来消除累积的导航漂移。最后，为了进一步提高系统的鲁棒性，低成本的惯性测量单元（IMU）和全球定位系统（GPS）传感器的测量值与视觉里程表集成在扩展的卡尔曼滤波框架中。在室内和室外的远距离导航中，我们的系统比以前发表的技术（1〜5％的定位误差）要准确，可靠得多。在人类佩戴的系统上进行的实际实验表明，无需使用GPS信息，就可以在500米的1米以内估计位置（平均定位误差约为0.1％）。

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