Name
Abstract | ||
|---|---|---|
While loading equipment into factories or facilities, pre-loading planning on computers to determine a loading object's posture and its loading path will help reduce trials and errors at the site location. During such pre-loading planning, we need to detect the shape data of both the factory area and loading object and their interference states and then plan the loading object's posture accordingly. In practice, however, there are a considerable number of issues while acquiring the latest factory area data and while grasping where the loading object in complex postures will result in interference, both simultaneously and for a short time period. In this study, we aimed at resolving the above-mentioned difficulties by developing a system that can detect where the loading object will interfere by means of polygonal shapes and can visualize the area by means of point clouds, both working in conjunction so that the developed system can automatically plan a loading object's posture and can visualize its planned posture through augmented reality. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.20965/ijat.2019.p0475 | INTERNATIONAL JOURNAL OF AUTOMATION TECHNOLOGY |
Keywords | Field | DocType |
augmented reality, point clouds, simultaneous localization and mapping (SLAM) | Systems engineering,Computer science,Support system,Augmented reality,Point cloud | Journal |
Volume | Issue | ISSN |
13 | 4 | 1881-7629 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takayuki Nakamura | 1 | 0 | 0.68 |
| junichi kaneko | 2 | 1 | 3.78 |
| Takeyuki Abe | 3 | 0 | 0.34 |
| kenichiro horio | 4 | 2 | 5.08 |