| Project/Area Number |
18500148
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | The University of Tokyo |
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Principal Investigator |
OTA Jun The University of Tokyo, Graduate School of Engineering, Associate Professor (50233127)
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| Co-Investigator(Kenkyū-buntansha) |
ARAI Tamio The University of Tokyo, Graduate School of Engineering, Professor (40111463)
YOKOI Hiroshi The University of Tokyo, Graduate School of Engineering, Associate Professor (90271634)
CHIBA Ryousuke The University of Tokyo, Graduate School of Engineering, Researcher (80396936)
UEDA Ryuuichi The University of Tokyo, Graduate School of Engineering, Assistant Professor (20376502)
杉 正夫 東京大学, 大学院情報理工学系研究科, 特任助手 (90372408)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥4,050,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥450,000)
Fiscal Year 2007: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2006: ¥2,100,000 (Direct Cost: ¥2,100,000)
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| Keywords | multiple robots / motion planning / grasping / role allotment / task constraints / 群知能ロボット / 作業割付 / 移動ロボット / 搬送 |
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| Research Abstract |
In former researches in mufti-robotics, in spite of its importance, there have been no propositions of task allocation scheme toward the problem involving "task constraints" that impose some restriction on the orders of task execution. In other studies involving task constraints such as job shop scheduling, task constraints are given by the designer. We address the problem that robots should calculate task constraints by themselves and should execute task allocation considering their constraints. As an example of such problem, we adopted rearrangement task of multiple movable objects. In this research, following subjects should be solved.
1. Task allocation should be executed considering task constraints.
2. Task constraints should be calculated as early as possible.
Toward these subjects, we have obtained following results.
1. By means of classification of task constraints, we have obtained calculation methods of task constraints and task allocation methods considering these constraints.
2. We have promoted efficiency of calculation procedure of task constraints. First, we have analyzed calculation procedure from viewpoints when calculation should be done and how long it should be taken. Next, we have listed all possible procedure. Finally, we have tested these procedures in simulated environments. As a result, following method turns out to be the most effective: In every time of task allocation, robots should calculate some constraints that costs comparatively low calculation costs. And robots should calculate other constraints that cost comparatively high calculation costs only when robots fail to planned tasks.
In future works, more flexible framework that divides given task into several small tasks is needed. For example, some objects should be temporarily set to adequate intermediate goals.
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