Ultra-High-speed Sensory-Motor System Based on Distributed Network Architecture

本研究的目的是开发一个在真实的环境中能够以灵活的方式高速行动的认知-行为整合系统。利用基于分层并行架构的感觉-运动集成、超高速识别和运动、分布式网络处理架构等基础技术，我们开发了一个基于分布式网络结构的高速实时处理系统，该系统将大量的传感器和执行器连接在一起。IP通信功能。为了在大范围内无遮挡地跟踪高速运动的多个目标，2.分布式传感器网络信息处理算法提出了一种传感器信息融合处理方法DTKF（Delay-Tolerant Kalman Filter）。DTKF是一种使用卡尔曼滤波的方法，它具有很好的可扩展性， ...更多信息 传感器数量的增加。通过对高速视觉传感器目标跟踪任务的数值仿真，验证了所提出方法的有效性。3.多高速视觉反馈系统设计了一个具有多个高速视觉的多高速视觉反馈系统。通过使用多个视觉系统对缺少的信息进行插值，实现了对遮挡具有鲁棒性的多目标三维跟踪。4.基于分层并行处理结构的传感-运动融合为了连接大量的传感器系统和机器人系统，我们开发了一个并行分布式处理系统，其中集成了实时处理系统、机器人系统和传感器系统。在该系统中，由dSpace公司制造的三个实时处理系统通过CAN总线相互连接，两个机械臂、三个机械手、三个高速视觉系统（六个摄像头）和其他传感器（触觉传感器、力传感器等）通过高速IO端口连接。少

The purpose of this study is to develop a recognition-behavior integration system which can act in a flexible manner at high-speed in the real environment. Using basic technologies, such as sensory-motor integration based on hierarchical parallel architecture, ultra-high-speed recognition and motion, and distributed network processing architecture, we have developed a high-speed realtime processing system in which a large number of sensors and actuators are connected based on distributed network architecture.1.A high-speed vision network system with TCP/IP communication function.In order to track many targets which moves at high-speed in a wide area without occlusion, we have developed a distributed cooperative network system with multiple vision systems.2.A distributed sensor network information processing algorithm.We have proposed a sensor fusion processing method called DTKF (Delay-Tolerant Kalman Filter). DTKF is a method using Kalman Filter, and it has a good scalability against … More the increase of the number of sensors. The proposed method was verified by a numerical simulation of a target tracking task of high-speed vision sensor.3.A multi-high-speed visual feedback system.We have developed a multi-high-speed visual feedback system with multiple high-speed visions. By interpolating the lack of information using several vision systems, a 3D tracking of multiple targets which is robust against occlusion is achieved. Also, the improvement of a range of measurement and accuracy, and occlusion avoidance is achieved.4.Sensory-motor fusion based on hierarchical parallel processing architectureIn order to connect a large number of sensor systems and robot systems, we have developed a parallel distributed processing system in which realtime processing systems, robot systems, and sensor systems are integrated. In the system three realtime processing systems made by dSpace Inc, are connected to each other using the CAN bus, and two robot arms, three robot hands, three high-speed vision systems (six camera heads), and other sensors (tactile sensors, force sensors, and so on) are connected with high-speed IO ports. Less