Synthetic Study of Imitation on Humans and Intelligent Robots

模仿人类与智能机器人的综合研究

基本信息

批准号：
13GS0006
负责人：
TOMOMASA Sato
金额：
$ 249.43万
依托单位：
The University of Tokyo
依托单位国家：
日本
项目类别：
Grant-in-Aid for Creative Scientific Research
财政年份：
2001
资助国家：
日本
起止时间：
2001 至 2005
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13GS0006/
关键词：
Imitation Integrated System Behavior Emergency Causality Recognition Intention Estimation Body Image Acquisition & Adaptation Learning from Observation Imitation by shape Behavior Imitation 模倣知能構成論的アプローチ動作認識全身行動インタラクティブ行動修正目

项目摘要

Imitation is the most fundamental intelligence as for the integrated behavior system of the cognitive brain functions and the developmental ability to learn new behaviors from man to adapt real environment. The following researches were conducted aiming at the science and technology of imitation. The following results would form not only the nucleus to develop new intelligent systems but also theoretical basis of cognitive science research fields.1) Construction of action observation and recognition systems :An environmental embedded system to measure human motions and a smart and flexible data management framework are developed. Based on the observation system, daily behavior pattern discovery, extraction methods, and robust action recognition frameworks based on statistical machine learning techniques with massive human motion data are presented and verified.2) Construction of action generation and correction systems :Humanoid behavior modification methods via evolutional approaches … More and human teaching assistance approaches are developed. In the latter approach, humanoid recognizes situations of the real world and learn what should be paid attention.3) Elucidation and modeling of human imitation function:Building synthetic functional map on imitation : This map clarifies several aspects of behavior imitation by making correspondence to brain functions. A theory for whole-body dynamic action that is called global dynamics mechanism is proposed and verified by analyzing rolling and rising motion of human and humanoid. Novel self-organizing network models are constructed representing several functions of brain from low-level visual perception to high-level context processing. Experimental studies on emergence of intelligence and development of cognition of human baby is executed.4) Experimental systems for realizing behavior imitation :Behavior imitation systems are realized based on humanoid and room-typed intelligent robot systems in order to verify the techniques proposed in the above research achievement (1-3) works well. The result implies that intelligent systems with the proposed human action observation and recognition methods, behavior generation and modification methods are proved to achieve goal-level imitation tasks. Less

模仿是人类认知大脑功能的综合行为系统和适应现实环境的学习新行为的能力的最基本智能，针对模仿科学技术进行了以下研究。不仅形成了开发新型智能系统的核心，而且成为认知科学研究领域的理论基础。1）动作观察和识别系统的构建：开发了一种测量人体运动的环境嵌入式系统和智能灵活的数据管理框架。关于观察系统、日常行为模式发现、提取方法、提出并验证了基于统计机器学习技术和大量人体运动数据的鲁棒动作识别框架。2）动作生成和校正系统的构建：通过进化方法的人形行为修改方法……更多以及人类教学辅助方法的开发。后一种方法，类人动物识别现实世界的情况并学习应该注意什么。3）人类模仿功能的阐明和建模：构建模仿的综合功能图：该图通过与大脑功能对应来阐明行为模仿的几个方面。一个理论通过分析人类和类人动物的滚动和上升运动，提出并验证了称为全局动力学机制的全身动态动作，构建了代表大脑从低级视觉感知到高级上下文的多种功能的新型自组织网络模型。对人类婴儿的智力出现和认知发展进行了实验研究。4）实现行为模仿的实验系统：基于类人和房间型智能机器人系统实现了行为模仿系统，以验证所提出的技术。上述研究成果（1-3）的结果表明，采用所提出的人类行为观察和识别方法、行为生成和修改方法的智能系统被证明能够实现目标级的模仿任务。

项目成果

期刊论文数量（336）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Real-time and Precise Self Collision Detection System for Humanoid Robots

DOI：
10.1109/robot.2005.1570256
发表时间：
2005-04
期刊：
Proceedings of the 2005 IEEE International Conference on Robotics and Automation
影响因子：
0
作者：
K. Okada;M. Inaba;H. Inoue
通讯作者：
K. Okada;M. Inaba;H. Inoue

國吉康夫: "AI事典第2版 (「模倣」および「環境との相互作用」の項目)"共立出版. 4 (2003)

Yasuo Kuniyoshi：“人工智能百科全书第二版（“模仿”和“与环境的相互作用”）”Kyoritsu Shuppan 4 (2003)。