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Combined Optic-Flow and Stereo-Based Navigation of Urban Canyons for a UAV

机译:联合光学流动和基于立体声的城市峡谷导航无人机

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We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereo-flow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images.
机译:我们提出了一种基于视觉的基于视觉的技术,用于通过城市峡谷导航无人驾驶飞行器(UAV)。我们的技术依赖于光学流程和立体声视觉信息。我们表明立体声和光学流动(立体流动)的组合在导航城市峡谷时比单独的技术更有效。来自一对侧面的照相机的光学流量用于保持在峡谷中的中心,并在连接点处启动转弯,而来自前部的立体声头的立体声视觉用于避免前面的障碍物全面测试技术在Csiro的自主拖拉机,部分在USC自主直升机上。实验结果由在室外环境中运行的这两个机器人平台提出。我们表明,自治拖拉机可以使用立体流动导航城市峡谷,并且自主直升机可以使用光学流动转向侧面的障碍物。此外,初步结果表明,一对正面的Fisheye相机可用于立体声和光学流动。鱼眼图像的中心部分用于立体声,而在图像的周边测量流程。

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