Acquisition and application using geometry big data by multiple robots with high-resolution laser scanner
| Project/Area Number |
26249029
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (A)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Intelligent mechanics/Mechanical systems
|
|---|
| Research Institution | Kyushu University |
|---|
Principal Investigator |
Kurazume Ryo 九州大学, システム情報科学研究院, 教授 (70272672)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
中澤 篤志 京都大学, 情報学研究科, 准教授 (20362593)
河村 晃宏 九州大学, システム情報科学研究院, 助教 (60706555)
諸岡 健一 九州大学, システム情報科学研究院, 准教授 (80323806)
辻 徳生 九州大学, システム情報科学研究科(研究院, 助教 (30403588)
岩下 友美 九州大学, システム情報科学研究科(研究院, 准教授 (70467877)
|
|---|
| Project Period (FY) |
2014-04-01 – 2018-03-31
|
| Project Status |
Completed (Fiscal Year 2017)
|
| Budget Amount *help |
¥40,950,000 (Direct Cost: ¥31,500,000、Indirect Cost: ¥9,450,000)
Fiscal Year 2017: ¥7,800,000 (Direct Cost: ¥6,000,000、Indirect Cost: ¥1,800,000)
Fiscal Year 2016: ¥9,880,000 (Direct Cost: ¥7,600,000、Indirect Cost: ¥2,280,000)
Fiscal Year 2015: ¥11,050,000 (Direct Cost: ¥8,500,000、Indirect Cost: ¥2,550,000)
Fiscal Year 2014: ¥12,220,000 (Direct Cost: ¥9,400,000、Indirect Cost: ¥2,820,000)
|
|---|
| Keywords | 知能ロボティクス / レーザ計測 / ビッグデータ / 環境モデリング / 空間知能化 |
|---|
| Outline of Final Research Achievements |
In this research, we developed a 3D scanning system using multiple robots named CPS-VIII, which combines the laser measurement technique using multiple robots called CPS-SLAM and a high-precision 3D laser scanner. This system is able to acquire geometrical big data consisting of trillions of 3D points. The experimental results showed that the accuracy for CPS-VIII is 0.0085 % of the distance traveled, which means the error is 0.0231 m after the robot moved 270.1 m. In addition, we developed large-scale geometrical big data of urban area and surrounding area of Fukuoka city and provided them on the web. Furthermore, we developed space/road categorization techniques for autonomous vehicles and mobile robots, and proposed high precision recognition techniques using convolutional neural networks and the combination of multiple machine learning techniques.
|
Report
(5 results)
Research Products
(37 results)
