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移动机器人电机控制与视觉跟踪导航关键技术研究
Alternative TitleResearch on Motor Control and Visual Tracking Navigation of Mobile Robots
陈晓鹏
Subtype工学博士
Thesis Advisor原魁 ; 李成荣
2008-05-29
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword移动机器人 无刷直流电机 电机控制 建模 动力学 均值移动 目标跟踪 目标检测 体系结构 行为导航 Mobile Robots Brushless Dc Motor Motor Control Modeling Dynamics Mean Shift Object Tracking Object Detection Architecture Behavior Navigation
Abstract在863课题“动态环境下的智能导览服务机器人关键技术与应用研究”经费支持下,本文以运行在室内动态环境的差分驱动轮式移动机器人为研究对象,对电机控制与视觉跟踪导航两个子问题展开深入研究。本文的主要内容和贡献如下: 研制一款基于AVR Mega48最大功率可达1500W的高性价比直流无刷电机驱动器,该驱动器三相桥臂驱动电路完全由分立元件组成。 针对质心位置任意的移动机器人建模问题,推导出它的运动学方程和动力学方程,推导出描述移动机器人动力学关系的两轮速度与电机转矩之间非线性微分方程。针对移动机器人电机控制问题,提出了DMMC控制方法,该法结合速度力矩间非线性微分方程和电机模型,建立了移动机器人系统状态方程,舍弃状态方程不可补偿非线性部分,设计I型状态反馈控制系统。仿真验证了算法的有效性。 提出一种自适应带宽均值移动新算法ABMS,该算法解决了普通均值移动算法带宽选择问题和带宽更新问题。针对二维应用推导了二维自适应带宽均值移动算法2D-ABMS。 把二维自适应带宽均值移动算法应用于目标跟踪,得到自适应带宽均值移动目标跟踪算法ABMSOT,该算法不仅能实时跟踪目标的位置,而且能实时跟踪目标的大小和方向。 把二维自适应带宽均值移动算法应用于目标检测,提出了一种自适应带宽均值移动目标检测算法ABMSOD。该算法不仅能检测物体的存在与否,而且能检测出物体在图象中的位置、大小和方向。 提出一种开放式、模块化的具有操作系统兼容性、设备兼容性、通信兼容性、数据接口兼容性的移动机器人体系结构,便于周期长的导航软件开发。基于此体系结构和开源软件ARIA,设计导航软件NAVOP,在此基础上采用自适应带宽均值移动目标跟踪和检测算法完成视觉跟踪导航实验。
Other AbstractFunded by 863 National High Tech Project “Research on Guide Service Mobile Robots with Dynamically Changed Environments”, this thesis focuses on differential wheeled mobile robots with dynamically changed indoor environment. The two research topics of this thesis are motor control and visual tracking navigation of differential wheeled mobile robots. The novel work and contribution of this thesis can be summarized as follows: A kind of brushless DC motor drives whose maximal power reaches up to 1500 walts are developed based on AVR Mega48 MCU. A novel analog mosfet bridge drive circuit used in the motor drives is presented. The kinematic model and dynamic model of mobile robots whose mass centers are not necessarily on the common axis of two driving wheels nor on the middle of two wheels are proposed. Based on the dynamic model, the differential equation between speeds and torques of two wheels are derived. The differential equations of two DC motors are adopted for the derivation of the state equation of mobile robots. A novel control law which is called DMMC (Dynamic Modeling based Motor Control of mobile robots) is proposed for controlling the two driving motors of differential mobile robots. Simulation shows that the DMMC controller responds to the inputs without static error. A novel adaptive bandwidth mean shift algorithm or ABMS is presented for solving the bandwidth selection problem and bandwidth updating problem in the classical mean shift algorithm. The adaptive bandwidth mean shift algorithm in 2D case or 2D-ABMS for short is thoroughly analysed. Based on the 2D adaptive bandwidth mean shift algorithm, a novel object tracking algorithm, which is called adaptive bandwidth mean shift object tracking algorithm or ABMSOT for short, is proposed. Experiments show that the ABMSOT is capable of simultaneously tracking the position, scale and rotation in real-time. Based on the 2D adaptive bandwidth mean shift algorithm, a novel adaptive bandwidth object detection algorithm, or ABMSOD for short, is proposed for object detection and localization. Experiments verify that the ABMSOD is not only able to detect the existence of certain objects, but also able to find the best position, scale and rotation of the objects in a given image. A novel open modular mobile robot software architecture with operating system compatibility, communication abstraction, device abstraction and interface specification is presented for long time navigation software developments. Based on the open modular software architecture, a navigation software NAVOP(NAVigation OPeration system) is developed with the help of ARIA. Tracking navigation experiments is fulfilled using ABMSOT and ABMSOD algorithm.
shelfnumXWLW1212
Other Identifier200618014628001
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6089
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
陈晓鹏. 移动机器人电机控制与视觉跟踪导航关键技术研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2008.
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