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摘要: 对于地面无人车和室外非结构化环境, 本文介绍了我们开发的基于立体视觉的障碍物快速识别系统. 为了使无人地面车适应于较复杂的地形, 根据V视差图, 我们提出了一种新的地面主视差图的估计方法. 通过地面主视差图和局部的三维重建, 本文给出了一种由粗到精的障碍物识别与定位方法. 在我们的无人地面车平台上, 我们对这一障碍物自动识别系统进行了相应的实际试验. 其试验结果验证了该系统的有效性.Abstract: This paper presents a fast obstacle detection system based on stereo vision for unmanned ground vehicle (UGV) navigation in unstructured environment. In order to make the UGV adaptable to more complex terrains, we propose a new estimation method of the main ground disparity (MGD) from the V-disparity images. Then, by comparing the disparity of the MGD with local 3D reconstruction, a coarse-to-fine method to find and localize obstacles is introduced in the paper. The obstacle detection system is tested practically on our UGV platform in some outdoor unstructured environments. The experimental results validate the efficacy of our system.
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