Name
Abstract | ||
|---|---|---|
Semantic maps are an important tool to provide robots with high-level knowledge about the environment, enabling them to better react to and interact with their surroundings. However, as a single measurement of the environment is solely a snapshot of a specific time, it does not necessarily reflect the underlying semantics. In this work, we propose a method to create a semantic map of a construction site by fusing multiple daily data. The construction site is measured by an unmanned aerial vehicle (UAV) equipped with a LiDAR. We extract clusters above ground level from the measurements and classify them using either a random forest or a deep learning based classifier. Furthermore, we combine the classification results of several measurements to generalize the classification of the single measurements and create a general semantic map of the working site. We measured two construction fields for our evaluation. The classification models can achieve an average intersection over union (IoU) score of 69.2% during classification on the Sanbongi field, which is used for training, validation and testing and an IoU score of 49.16% on a hold-out testing field. In a final step, we show how the semantic map can be employed to suggest a parking spot for a dump truck, and in addition, show that the semantic map can be utilized to improve path planning inside the construction site. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/LRA.2021.3062606 | IEEE ROBOTICS AND AUTOMATION LETTERS |
Keywords | DocType | Volume |
Semantics, Robots, Three-dimensional displays, Image segmentation, Laser radar, Random forests, Data mining, Field robots, robotics and automation in construction, semantic scene understanding | Journal | 6 |
Issue | ISSN | Citations |
2 | 2377-3766 | 0 |
PageRank | References | Authors |
0.34 | 10 | 15 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thomas Westfechtel | 1 | 6 | 3.55 |
| Kazunori Ohno | 2 | 264 | 40.48 |
| Tetsu Akegawa | 3 | 0 | 0.34 |
| Kento Yamada | 4 | 6 | 2.92 |
| Ranulfo Plutarco Bezerra Neto | 5 | 3 | 2.12 |
| Shotaro Kojima | 6 | 4 | 5.19 |
| Taro Suzuki | 7 | 32 | 6.65 |
| Tomohiro Komatsu | 8 | 3 | 1.78 |
| Yukinori Shibata | 9 | 3 | 1.78 |
| Kimitaka Asano | 10 | 3 | 1.78 |
| Keiji Nagatani | 11 | 0 | 1.01 |
| Naoto Miyamoto | 12 | 3 | 1.44 |
| Takahiro Suzuki | 13 | 11 | 4.38 |
| Tatsuya Harada | 14 | 508 | 71.32 |
| Satoshi Tadokoro | 15 | 1014 | 177.55 |