遥控“动物机器人”技术及其神经信息处理
文献类型：学位论文
| 作者 | 宋卫国 |
| 学位类别 | 工学博士 |
| 答辩日期 | 2006-05-26 |
| 授予单位 | 中国科学院研究生院 |
| 授予地点 | 中国科学院自动化研究所 |
| 导师 | 原魁 |
| 关键词 | 动物机器人 脑机接口 神经信息处理 动作电位检测及分类 触觉建模 animal robotics brain-machine interface neural signal processing spike detection and sorting haptic modeling |
| 其他题名 | Remote controlled “Animal Robotics” and related neural signal processing |
| 学位专业 | 控制理论与控制工程 |
| 中文摘要 | 本文针对“动物机器人”技术及应用平台进行了较为深入的研究，即利用动物作为运动本体，背负或在身体内埋置电子电路、传感器等装置，经过一定的训练，通过遥控方式控制动物的运动行为，来得到所需的信息或完成某种任务。本研究不仅对基础研究、临床应用具有重要的意义，而且可以用作搜救、排爆等方面具有工程及军事价值。 主要研究内容及成果如下： 1.研制了用于训练“动物机器人”的便携式多模式刺激器以及动物行为监控分析系统，实验表明，该系统适用于神经行为学的相关研究。 2.提出了混合声音条件刺激及神经电刺激的“动物机器人”训练方法，并初步训练出“动物机器人”原型；设计了神经信息无线采集系统以及微推进电极，具有简单、廉价、实用等特点。 3.研究了基于连续小波变换及平滑非线性能量算子的检测方法，实验表明本算法具有较好的稳定性及有效性。 4.提出了一种新的基于小波包及自适应模糊推理系统(ANFIS)的动作电位的分类方法，并通过实验对其有效性进行了验证。 5.基于图像及三维磁跟踪的方法，设计了生物组织切割过程的多参量采集系统；进而提出了一种基于模糊规则来建立切割触觉模型方法；并对集成此模型的触觉手术刀模拟系统进行了描述并对其有效性进行了初步的验证。 |
| 英文摘要 | A series of attempts were explored in this dissertation in order to a research on “animal-robotics”. That is, by carrying or implanted with electronic devices or sensors, animals are remotely controlled to perform specific task and act as robot. The research on the “animal-robotics” is not only important value in base science research, but also opens new possibilities for clinical applications. It also has a practical and the military value in searching victims from earthquakes or bombings. The main contents and achievements of this dissertation are as follows: (1)An experimental platform for “animal-robotic” training was developed by integrating a multimode micro-stimulator with a machine vision based animal behavior tracking device, which provides a platform for behavioral neuroscience researches. (2)A new “animal robotic” training method, which integrates with both sound cue and electrical stimulation, was presented, and a prototype ‘rat-robotic’ was trained successfully. A micro-drive electrode and real time neural signal acquisition device was developed with notable characteristics of simplicity and practicality. (3)A novel spike detection algorithm is presented by combining multi-resolution analysis and smoothed nonlinear energy operator. Preliminary results from extracellular recording of rat brain show that it is efficient and robust for spike detecting even under low signal-to-noise ratio. (4)A new spike sorting algorithm is presented by combining wavelet packet and adaptive neural fuzzy inference system (ANFIS). Results from extracellular recordings show that this method is efficient and robust for spike sorting under low signal-to-noise ratio. (5)Based on image processing and magnetic tracking method, a haptic acquisition system for soft tissue cutting was designed. Then, haptic modeling based on fuzzy rules was given, and a haptic scalpel integrated with the established fuzzy model was presented, and the preliminary results showed its efficacy for cutting simulation. |
| 语种 | 中文 |
| 其他标识符 | 200318014602984 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/5899]  |
| 专题 | 毕业生_博士学位论文 |
| 推荐引用方式 GB/T 7714 | 宋卫国. 遥控“动物机器人”技术及其神经信息处理[D]. 中国科学院自动化研究所. 中国科学院研究生院. 2006. |
入库方式： OAI收割
来源：自动化研究所
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