基于毫米级移动微机器人的微装配系统运动控制与路径规划研究
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摘要
随着移动微机器人技术的发展,其各方面的性能都得到了很大提高,尤其在运动灵活性和运动精度方面。相应地,基于移动微机器人的应用研究也逐渐开展起来。其中,利用移动微机器人进行微小零件的装配操作研究受到了很多关注。
在国家相关项目的资助下,课题组研制了毫米级全方位移动微机器人,并搭建了基于微机器人的微装配系统,进行了零件微装配操作的探索性研究。对微装配系统而言,微装配的准确度和精度是重要的性能指标。目前,该系统在微机器人运动控制和微装配路径规划的一些方面存在不足,影响了微装配的准确度和精度。因此,本文以基于移动微机器人的微装配系统作为研究平台,对微机器人运动控制和装配路径规划中涉及的一些问题展开研究,目的是提高系统微装配的准确度和精度,为实现精密的微装配操作奠定基础。
运动控制研究是进行微装配路径规划研究的基础。运动控制研究包括微机器人的轮结构尺寸设计、运动特性、滑动和稳定步进等。微装配路径规划研究则包括智能路径搜索方法、微机器人状态空间划分方法以及构建路径规划知识库等。
微机器人动力学分析推导出了运动所需微马达转矩与轮结构尺寸之间的函数关系式,以该关系式作为目标函数,以最小化微马达转矩消耗作为优化目标,利用遗传算法对微机器人轮结构尺寸进行了设计。实验表明微机器人具有良好的驱动能力,从而为运动控制提供了动力保障。
对微机器人的运动学进行了较为全面的研究。针对微机器人的特殊结构,采用求解、分析运动学约束矩阵秩的方法,阐明了其机动性和全方位特性,为微机器人的结构设计和控制提供了理论依据。此外,分别建立了微机器人本体运动学方程和微装配手臂运动学方程,利用推导的雅克比矩阵分析了微机器人的运动特点,分析结果与实际情况一致。
建立了微机器人滑动动力学模型。从微机器人结构特点出发,分析了产生滑动的三种因素及其滑动效果,并基于滑动动力学模型进行了滑动效果的仿真验证。采用了基于视觉反馈控制的滑动克服方法,以减小滑动造成的运动偏移,仿真验证了控制效果。
分析了基于转矩自平衡特性的微马达步进定位原理,推导了用于微机器人步进驱动的转矩表达式。基于微机器人动力学方程建立了步进运动仿真模型,并对步进运动过程进行了仿真研究。研究表明微马达转矩对步进稳定性有较大影响,针对这一的情况,采用了反馈控制微马达电流的方法来实现微机器人较为稳定的步进和均匀的步距。
微机器人携带零件前往微装配区域进行装配操作涉及到运动路线的选择问题,常规路径规划方法不能实现较高的微装配准确度和精度。因此设计了一种监督—增强式混合学习方法,并将其应用到微装配操作的路径规划中。该方法以增强式学习算法为主体,以监督学习算法为辅助。同常规方法和单一的增强式学习方法相比,该混合学习方法实现了较高的微装配准确度和精度。此外,设计了三种微机器人状态空间的划分模型,分别称为均匀Grid-tile模型、非均匀Grid-tile模型和蛛网形Tile模型,并比较了它们的应用效果。比较结果显示后两种模型的学习效率远远高于第一种,其中蛛网形模型的性能最好。最后,构建了路径规划知识库,用于提高在线路径规划的速度。
总之,本文的研究针对一种基于毫米级移动微机器人的微装配系统,对其运动控制与路径规划中存在的一些问题进行了分析,提出了相应的解决方法,并进行了仿真或实验验证,也取得了一定的成果。但在一些方面还需进一步研究,如多移动微机器人协作微装配等。
With the technology development of mobile microrobot, various performances of the mobile microrobot are improved greatly, especially on the mobility and motion precision. Relatively, the mobile microrobot based application researches become warm and warm. And much attention is paid on the micro parts assembly using mobile microrobot.
Supported by research programs of China, our research team designs the millimeter size omnidirectional mobile microrobots, and develops the microrobot based microassembly system. The exploratory research on the micro parts microassembly with this system has carried on. For a microassembly system, the microassembly accuracy and precision are important performance indices. At present, there are some drawbacks on the aspects of microrobot motion control and microassembly path planning method, which influences the microassembly accuracy and precision. This paper presents the microrobot motion control and microassembly path planning of the microassembly system. The research objective is to improve the microassembly accuracy and precision, and to lay a foundation for realizing the precise microassembly operation.
The research on motion control is the foundation of microassembly path planning research. The motion control research includes the wheel structure size design, motion characteristic, slip and stable step movement. The path planning research includes the intelligent path searching method, and partitioning of microrobot state space and path planning knowledge database.
The dynamic analysis derives the function relationship between the needed micromotor torque for movement driving and the wheel structure sizes. Therefore, the genetic algorithm (GA) is employed to design the wheel structure sizes. The target function of GA is the relation equation of the torque and wheel sizes, and the optimal target is to minimize the torque consumption. The experiments show that the microrobots have good driving ability, which provides the guarantee of motion control.
This paper presents more comprehensive research on the microrobot kinematics. Considering the microrobot special structure, the kinematic constraint matrix is derived and employed to analyze the maneuverability and omnidirectional characteristic. Besides, the kinematic equations of the microrobot chassis and microassembly arm are found. And the Jacobian matrixs are derived and used to analyze the microrobot and arm motion characteristics, and the analyzed results are same as the real
? Supported by National Natural Science Foundation of China (No. 60475037), and Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20060248057), Hi-Tech Research and Development Program of China (No. 2007AA04Z340). situation.
The microrobot slip dynamic model is found. According to the microrobot structure characteristic, three factors which can generate slip are analyzed, and their slip effects are also analyzed and demonstrated based on the slip dynamic model. A vision based slip control method is developed to reduce the motion deviation.
The micromotor step positioning principle based on torque self balance is analyzed, and then the torque expression for microrobot step movement driving is drived. The simulation model of step movement is found based on the microrobot dynamic equation. With this model, the step movement process is simulated. The simulation shows that the micromotor torque has great influence on the step movement stability. Therefore, the feedback control of micromotor current is used to obtain stable step movement and uniform step displacement.
There is the problem of motion path selection during the microassembly process. The conventional path planning method can not ensure high microassembly accuracy and precision. Therefore, a mixed learning method that integrates the supervised learning and the reinforcement learning is developed and then employed for the microassembly path planning. Compared with the conventional method and the single reinforcement learning, the mixed learning method achieves higher microassembly accuracy and precision. Three models, named uniform grid tile, uneven grid tile and cobweb tile, are designed to partition the microrobot state space. Their application effects are compared, which show that the learning efficiencies of the later two models are much higher than that of the first model. The performance of the cobweb tile is best. Finally, the path planning knowledge database is found to improve the on-line path planning speed.
Above all, according to the millimeter size microrobot based microassembly system, this paper presents the microrobot motion control and microassembly path planning. Some problems of them are analyzed, and relative solutions are developed and then demonstrated by simulations or experiments. Though some achievements are obtained, deep research is needed on some directions, e.g. multi microrobots cooperation for microassembly.
在国家相关项目的资助下,课题组研制了毫米级全方位移动微机器人,并搭建了基于微机器人的微装配系统,进行了零件微装配操作的探索性研究。对微装配系统而言,微装配的准确度和精度是重要的性能指标。目前,该系统在微机器人运动控制和微装配路径规划的一些方面存在不足,影响了微装配的准确度和精度。因此,本文以基于移动微机器人的微装配系统作为研究平台,对微机器人运动控制和装配路径规划中涉及的一些问题展开研究,目的是提高系统微装配的准确度和精度,为实现精密的微装配操作奠定基础。
运动控制研究是进行微装配路径规划研究的基础。运动控制研究包括微机器人的轮结构尺寸设计、运动特性、滑动和稳定步进等。微装配路径规划研究则包括智能路径搜索方法、微机器人状态空间划分方法以及构建路径规划知识库等。
微机器人动力学分析推导出了运动所需微马达转矩与轮结构尺寸之间的函数关系式,以该关系式作为目标函数,以最小化微马达转矩消耗作为优化目标,利用遗传算法对微机器人轮结构尺寸进行了设计。实验表明微机器人具有良好的驱动能力,从而为运动控制提供了动力保障。
对微机器人的运动学进行了较为全面的研究。针对微机器人的特殊结构,采用求解、分析运动学约束矩阵秩的方法,阐明了其机动性和全方位特性,为微机器人的结构设计和控制提供了理论依据。此外,分别建立了微机器人本体运动学方程和微装配手臂运动学方程,利用推导的雅克比矩阵分析了微机器人的运动特点,分析结果与实际情况一致。
建立了微机器人滑动动力学模型。从微机器人结构特点出发,分析了产生滑动的三种因素及其滑动效果,并基于滑动动力学模型进行了滑动效果的仿真验证。采用了基于视觉反馈控制的滑动克服方法,以减小滑动造成的运动偏移,仿真验证了控制效果。
分析了基于转矩自平衡特性的微马达步进定位原理,推导了用于微机器人步进驱动的转矩表达式。基于微机器人动力学方程建立了步进运动仿真模型,并对步进运动过程进行了仿真研究。研究表明微马达转矩对步进稳定性有较大影响,针对这一的情况,采用了反馈控制微马达电流的方法来实现微机器人较为稳定的步进和均匀的步距。
微机器人携带零件前往微装配区域进行装配操作涉及到运动路线的选择问题,常规路径规划方法不能实现较高的微装配准确度和精度。因此设计了一种监督—增强式混合学习方法,并将其应用到微装配操作的路径规划中。该方法以增强式学习算法为主体,以监督学习算法为辅助。同常规方法和单一的增强式学习方法相比,该混合学习方法实现了较高的微装配准确度和精度。此外,设计了三种微机器人状态空间的划分模型,分别称为均匀Grid-tile模型、非均匀Grid-tile模型和蛛网形Tile模型,并比较了它们的应用效果。比较结果显示后两种模型的学习效率远远高于第一种,其中蛛网形模型的性能最好。最后,构建了路径规划知识库,用于提高在线路径规划的速度。
总之,本文的研究针对一种基于毫米级移动微机器人的微装配系统,对其运动控制与路径规划中存在的一些问题进行了分析,提出了相应的解决方法,并进行了仿真或实验验证,也取得了一定的成果。但在一些方面还需进一步研究,如多移动微机器人协作微装配等。
With the technology development of mobile microrobot, various performances of the mobile microrobot are improved greatly, especially on the mobility and motion precision. Relatively, the mobile microrobot based application researches become warm and warm. And much attention is paid on the micro parts assembly using mobile microrobot.
Supported by research programs of China, our research team designs the millimeter size omnidirectional mobile microrobots, and develops the microrobot based microassembly system. The exploratory research on the micro parts microassembly with this system has carried on. For a microassembly system, the microassembly accuracy and precision are important performance indices. At present, there are some drawbacks on the aspects of microrobot motion control and microassembly path planning method, which influences the microassembly accuracy and precision. This paper presents the microrobot motion control and microassembly path planning of the microassembly system. The research objective is to improve the microassembly accuracy and precision, and to lay a foundation for realizing the precise microassembly operation.
The research on motion control is the foundation of microassembly path planning research. The motion control research includes the wheel structure size design, motion characteristic, slip and stable step movement. The path planning research includes the intelligent path searching method, and partitioning of microrobot state space and path planning knowledge database.
The dynamic analysis derives the function relationship between the needed micromotor torque for movement driving and the wheel structure sizes. Therefore, the genetic algorithm (GA) is employed to design the wheel structure sizes. The target function of GA is the relation equation of the torque and wheel sizes, and the optimal target is to minimize the torque consumption. The experiments show that the microrobots have good driving ability, which provides the guarantee of motion control.
This paper presents more comprehensive research on the microrobot kinematics. Considering the microrobot special structure, the kinematic constraint matrix is derived and employed to analyze the maneuverability and omnidirectional characteristic. Besides, the kinematic equations of the microrobot chassis and microassembly arm are found. And the Jacobian matrixs are derived and used to analyze the microrobot and arm motion characteristics, and the analyzed results are same as the real
? Supported by National Natural Science Foundation of China (No. 60475037), and Specialized Research Fund for the Doctoral Program of Higher Education of China (No.20060248057), Hi-Tech Research and Development Program of China (No. 2007AA04Z340). situation.
The microrobot slip dynamic model is found. According to the microrobot structure characteristic, three factors which can generate slip are analyzed, and their slip effects are also analyzed and demonstrated based on the slip dynamic model. A vision based slip control method is developed to reduce the motion deviation.
The micromotor step positioning principle based on torque self balance is analyzed, and then the torque expression for microrobot step movement driving is drived. The simulation model of step movement is found based on the microrobot dynamic equation. With this model, the step movement process is simulated. The simulation shows that the micromotor torque has great influence on the step movement stability. Therefore, the feedback control of micromotor current is used to obtain stable step movement and uniform step displacement.
There is the problem of motion path selection during the microassembly process. The conventional path planning method can not ensure high microassembly accuracy and precision. Therefore, a mixed learning method that integrates the supervised learning and the reinforcement learning is developed and then employed for the microassembly path planning. Compared with the conventional method and the single reinforcement learning, the mixed learning method achieves higher microassembly accuracy and precision. Three models, named uniform grid tile, uneven grid tile and cobweb tile, are designed to partition the microrobot state space. Their application effects are compared, which show that the learning efficiencies of the later two models are much higher than that of the first model. The performance of the cobweb tile is best. Finally, the path planning knowledge database is found to improve the on-line path planning speed.
Above all, according to the millimeter size microrobot based microassembly system, this paper presents the microrobot motion control and microassembly path planning. Some problems of them are analyzed, and relative solutions are developed and then demonstrated by simulations or experiments. Though some achievements are obtained, deep research is needed on some directions, e.g. multi microrobots cooperation for microassembly.
引文
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