Abstract
<p>This research aims to develop a high-speed spatial change detection technique using point clouds and NDT (Normal Distribution Transformation). Point cloud obtained from a range sensor such as a RGB-D camera is transformed to voxel representation using NDT, and aligned and compared with map data measured by a high-precision laser scanner. Three techniques are introduced to make the proposed system robust for noise, that is, classification of point distribution, overlapping of voxels, and voting using consecutive sensing.</p>
| Translated title of the contribution | High-speed spatial change detection using point clouds and NDT |
|---|---|
| Original language | Japanese |
| Pages (from-to) | 2A2-O08 |
| Journal | ロボティクス・メカトロニクス講演会講演概要集 |
| Volume | 2017 |
| Issue number | 0 |
| DOIs | |
| Publication status | Published - 2017 |