【作者】 王婷婷；

【导师】 郭伟；

【作者基本信息】 哈尔滨工业大学 ， 机械电子工程， 2007， 硕士

【摘要】 仿生控制的研究对于机器人技术的进展有着重大的意义。近年来,模拟生物中枢模式发生器(CPG)的仿生控制已经成为仿生控制领域的研究热点之一。CPG能够在缺乏高层控制信号和外部反馈的情况下,自发产生稳定的节律性运动,这一运动具有易被高层命令调节、耦合性强、适应性强、结构简单等优点,可以减少控制系统的工作量,节约工作时间。目前,这一仿生控制的研究在国际上尚处于初级阶段,特别在结构的简单化、高层调节机制的加入等方面还不能很好地模拟生物的特性,充分发挥这一控制的优点。本文根据基于振动理论的三神经元CPG局部神经元网络数学模型建立了一种新的CPG控制模型,并针对机器人双关节的控制,以CPG控制模型为主体建立了双关节仿生控制系统。首先,根据三神经元CPG局部神经元网络数学模型,模拟生物神经系统中各神经元的响应原理,建立了各神经元的控制模型,分别实现节律运动的发生、反馈信息的传导与被控对象的驱动三项功能,并在仿真平台上对模型的控制特性做出验证。仿真结果表明,控制模型可以较好地模拟生物神经元的特性。其次,引入了仿生控制系统的概念,模拟生物的神经-肌肉控制系统建立了CPG仿生控制系统。通过CPG规划器、驱动神经元前项通道、反馈神经元通道的建立实现整个系统的运动模式发生、控制对象驱动与外界信息反馈,并通过这三个部分的连接与相互作用实现运动的简单高层控制信息与反馈信息调节。然后,模拟生物神经的整合作用,在单关节运动控制系统的基础上建立了机器人双关节耦合控制系统。通过控制系统自抑制系数的改变,实现了单CPG对双关节的耦合控制,并可通过简单高层控制信息对此运动进行调节。最后,应用此系统进行了单关节控制、双关节耦合控制与反射作用模拟等仿真实验。实验结果表明,此系统可较好地模拟生物特性,完成双关节耦合节律性运动的发生,并能通过较为简单的结构实现运动的高层调节以及生物反射作用的模拟。更多还原

【Abstract】 Bionic control is of great significance for the progress of robot technology. In recent years, bionic control based on central pattern generator (CPG) has become one of the hot spots of the field of bionic control. CPG can produce movement of spontaneous steady rhythm which is susceptible to high-level orders regulating, has strong coupling, multi-mode, strong adaptability and simple structure to the lack of high-level external control signal and the feedback, it can reduce the workload of the control system, saving hours of work. Currently, the research of the bionic control of CPG in the international arena is still at the preliminary stage. The control systems can not well simulate biological characteristics nor give full play to the advantage of this control method, particularly in the aspect of simplified structure, movement of Multi-mode and to follow high-level mechanism.Based on the three local neurons network model of CPG adopted the theory of vibration, we established a new control system model of CPG. Aimed at the control of a single leg of two joints of the robot, we built a single legged bionic control system of two joints which contains CPG as a primary part.First, We built the models of each neuron in the control system simulating the response theory of neurons in the biological nervous system according to the three local neurons network model of CPG adopted the theory of vibration. The neuron models achieve the rhythmic motion, feedback to the conduction and the object-driven respectively. Then validated the control characteristics on the simulation platform. Simulation results show that the model can simulate the biological characteristics of neurons preferably.Secondly, the paper simulated biological nerve-muscle control system to establish a single joint multi-loop bionic control system. We established the producing of the movement mode, the driving of the objects, the feeding back of the information by building the planner, the forward path and the feedback path, and established the interaction of high-level campaign to achieve control and feedback regulation with this three-part connection.Then, with the simulation of biological neural integration, this paper built a coupling control system of a single robot leg of two joints based on the single joint control system. The system can realize coupling control of two joints using only one CPG, with the adoption of high-level multi-regulating control system.Finally, we conducted a single joint control, a coupling control of two joints and simulation of reflection with the application of this system. Experimental results show that this system can accomplish double coupling joints rhythm movements simulating biological characteristics, and can achieve movements changing, high-level regulation of the movements and reflection simulation with a relatively simple structure.更多还原