Project/Area Number |
13650279
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Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Intelligent mechanics/Mechanical systems
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Research Institution | Osaka University |
Principal Investigator |
MIURA Jun Associate Professor, Graduate School of Engineering, Osaka University, 大学院・工学研究科, 助教授 (90219585)
|
Co-Investigator(Kenkyū-buntansha) |
SAKIYAMA Takuro Research Associate, Graduate School of Engineering, Osaka University, 大学院・工学研究科, 助手 (70335371)
SHIMADA Nobutaka Associate Professor Graduate School of Engineering, Osaka University, 大学院・工学研究科, 助教授 (10294034)
SHIRAI Yoshiaki Professor Gradnate School of Engineering, Osaka University, 大学院・工学研究科, 教授 (50206273)
|
Project Period (FY) |
2001 – 2002
|
Project Status |
Completed (Fiscal Year 2002)
|
Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2002: ¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 2001: ¥1,900,000 (Direct Cost: ¥1,900,000)
|
Keywords | Personal service robot / Object model generation and recognition / Interactive object recognition / Dialog generation / Robust speech recognition / Teaching / Mobile manipulator / 物体認識 / インタラクティブビジョン / 会話認識 / 辞書獲得 / センサベーストマニピュレーション / 作業移動ロボット |
Research Abstract |
As we are facing the "aging society", the need for such personal service robots which can help human in various everyday situations is increasing. We are developing a prototype of personal service robot that is able to fetch a can from a distant refrigerator. We have performed the research on the following functions required for such service robots: Easy teaching of mobile manipulator: Usually service robots have to deal with much wider range of tasks than industrial ones. An easy, user-friendly teaching method is, therefore, desirable for such service robots. We developed the following teaching method. A user teaches the robot a nominal trajectory of the hand and its tolerance to achieve a task. The robot searches for a feasible trajectory within the given tolerance; it also generates the movement of the mobile base if necessary. Since the user only needs to consider the movement of the hand, the method is well intuitive and does not require much effort from a user; in addition, the robot does not need much computation for trajectory generation because a nominal trajectory is given. Interactive object recognition: The robot basically recognizes cans and bottles using color information. If the robot failed to find a target object, it tries to obtain additional information by a dialog with a user. The robot generates a good question which can retrive informative answers from the user; this is a key to a smooth interaction between the robot aud the user. Robust speech recognition: Many existing dialog-based interface systems assume that a speech recognition (sub)system always works well. However, since the dialog with a robot is usually held in environments where various noises exist, such an assumption cannot be made. We have developed a method for estimating the meaning of unidentified words from the (mistakenly) recognized words, the identified words before and after the unidentified one, and the state of the dialog.
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