دورية أكاديمية
Data Structure for Efficient Processing in 3-D
| العنوان: | Data Structure for Efficient Processing in 3-D |
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| المؤلفون: | Jean-Francois Lalonde, Nicolas Vandapel, Martial Hebert |
| سنة النشر: | 2018 |
| المجموعة: | KiltHub Research from Carnegie Mellon University |
| مصطلحات موضوعية: | Adaptive Agents and Intelligent Robotics, Robotics |
| الوصف: | Autonomous navigation in natural environment requires three-dimensional (3-D) scene representation and interpretation. High density laser-based sensing is commonly used to capture the geometry of the scene, producing large amount of 3-D points with variable spatial density. We proposed a terrain classification method using such data. The approach relies on the computation of local features in 3-D using a support volume and belongs, as such, to a larger class of computational problems where range searches are necessary. This operation on traditional data structure is very expensive and, in this paper, we present an approach to address this issue. The method relies on reusing already computed data as the terrain classification process progresses over the environment representation. We present results that show significant speed improvement using ladar data collected in various environments with a ground mobile robot. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| العلاقة: | https://figshare.com/articles/Data_Structure_for_Efficient_Processing_in_3-D/6552482Test |
| DOI: | 10.1184/r1/6552482.v1 |
| الإتاحة: | https://doi.org/10.1184/r1/6552482.v1Test https://figshare.com/articles/Data_Structure_for_Efficient_Processing_in_3-D/6552482Test |
| حقوق: | In Copyright |
| رقم الانضمام: | edsbas.C2F6AC7 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1184/r1/6552482.v1 |
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