| Project/Area Number |
25330305
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Intelligent robotics
|
|---|
| Research Institution | Shizuoka University |
|---|
Principal Investigator |
|
|---|
| Co-Investigator(Renkei-kenkyūsha) |
KANEKO Toru 静岡大学, 工学部, 名誉教授 (50293600)
|
|---|
| Research Collaborator |
BEKHTI Mohammed Abdessamad
MATSUMURA Kazuki
MATSUNAGA Sho
|
|---|
| Project Period (FY) |
2013-04-01 – 2016-03-31
|
| Project Status |
Completed (Fiscal Year 2015)
|
| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
|
|---|
| Keywords | 移動ロボット / ナビゲーション / 屋外不整地 / 環境認識 / 屋外環境 / 画像認識 / 走行経験 / 加速度情報 / 画像特徴 / 不整地走行 |
|---|
| Outline of Final Research Achievements |
Autonomous robots are required to be able to act in environments which are not structured specifically for them. To meet the requirement, it is important to develop a technology which allows to adapt to unexperienced environment autonomously, instead of relying on human designers’ preparation under assumption or restriction of environment. In this research, an experience-based method for prediction of motion feature obtained by acceleration sensor was developed. The method was implemented on an outdoor autonomous robot and verified through experiment with uneven outdoor terrains. It was confirmed that it was possible to predict motion features based on information obtained by cameras attached to the robot. In addition, a motion planning scheme which allows consideration of velocity-dependent traversability assessment was proposed. We realized a navigation of a mobile robot to reach a destination while appropriately adjusting its velocity so as to avoid excessive accelerations.
|
