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首页> 外文期刊>Applied optics >Dense range map reconstruction from a versatile robotic sensor system with an active trinocular vision and a passive binocular vision
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Dense range map reconstruction from a versatile robotic sensor system with an active trinocular vision and a passive binocular vision

机译：从具有主动三目视觉和被动双目视觉的多功能机器人传感器系统进行密集距离图重建

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摘要

One major research issue associated with 3D perception by robotic systems is the creation of efficient sensor systems that can generate dense range maps reliably A visual sensor system for robotic applications is developed that is inherently equipped with two types of sensor, an active trinocular vision and a passive stereo vision. Unlike in conventional active vision systems that use a large number of images with variations of projected patterns for dense range map acquisition or from conventional passive vision system is that work well on specific environments with sufficient feature information, a cooperative bidirectional sensor fusion method for this visual sensor system enables us to acquire a reliable dense range map using active and passive information simultaneously. The fusion algorithms are composed of two parts, one in which the passive stereo vision helps active vision and the other in which the active trinocular vision helps the passive one. The first part matches the laser patterns in stereo laser images with the help of intensity images; the second part utilizes an information fusion technique using the dynamic programming method in which image regions between laser patterns are matched pixel-by-pixel with help of the fusion results obtained in the first part. To determine how the proposed sensor system and fusion algorithms can work in real applications, the sensor system is implemented on a robotic system, a ad the proposed algorithms are applied. A series of experimental tests is performed for a variety of configurations of robot and environments. The performance of the sensor system is discussed in detail. (c) 2008 Optical Society of America.
机译：机器人系统与3D感知相关的一个主要研究问题是创建可以可靠地生成密集距离图的高效传感器系统。开发了一种用于机器人应用的视觉传感器系统，该系统固有地配备了两种类型的传感器：主动三目视觉和被动立体视觉。不同于传统的主动视觉系统，该系统使用大量具有不同投影模式的图像进行密集范围地图采集，或者不同于传统的被动视觉系统，因为它在具有足够特征信息的特定环境下可以很好地工作，因此，一种用于此视觉系统的协作双向传感器融合方法传感器系统使我们能够同时使用主动和被动信息来获取可靠的密集范围图。融合算法由两部分组成，其中被动立体视觉有助于主动视觉，另一部分主动三目视觉有助于被动视觉。第一部分借助强度图像将立体激光图像中的激光图案进行匹配;第二部分利用信息融合技术，该技术采用动态编程方法，其中借助第一部分中获得的融合结果，将激光图案之间的图像区域逐像素匹配。为了确定所提出的传感器系统和融合算法如何在实际应用中工作，将传感器系统实现在机器人系统上，然后应用所提出的算法。针对机器人和环境的各种配置执行了一系列实验测试。详细讨论了传感器系统的性能。 （c）2008年美国眼镜学会。

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