微小气动机器人移动FSM建模与控制

根据仿生尺蠖运动机理研制了一种用于人体腔道微创诊查的微小机器人系统,该机器人系统由前支撑单元、后支撑单元和具有3个气室的橡胶驱动器三部分组成.根据微型机器人的本体结构分析了机器人的移动控制原理,给出了在一个运动循环周期内机器人移动一个步距的运动状态和控制时序.阐述了有限状态机原理,并基于有限状态机原理建立了该机器人移动...     

气动机器人电-气控制系统设计

研制了一种适用于人体内腔诊查的柔性气动微机器人系统,根据机器人机体结构和移动机理,设计了该机器人的电-气控制系统,通过该控制系统控制机器人的主动移动,完成人体内腔的环境参数监测与诊疗等任务.     

基于神经网络PID控制的柔性微机器人系统

根据尺蠖蠕动的原理,研制了一种三自由度微型机器人内窥镜诊疗系统;该机器人由空气压橡胶驱动器驱动,通过两个气囊钳位．建立了机器人的动态模型．基于BP神经网络PID控制策略,设计了电—气脉宽调制伺服系统控制机器人的移动．用系统输出的预测值来代替实测值,计算权系数的修正量,实时改变控制参数以提高控制效果．软件仿真和实验结果都证实该方法弥补了传统PID控制方法的不足,显著改善了系统的静动态特性,是一种理想的气动微型蠕动机器人控制方法．     

搜救机器人运动机理分析与仿真研究

为了开发一种能够在废墟狭窄空间中运动的搜救机器人,模仿尺蠖结构和运动特征,提出了具有多自由度易变形的仿生尺蠖移动机器人。搜救机器人在灾难现场运动时环境复杂、障碍物多,针对机器人在瓦砾狭小的空间移动运动策略较难确定的问题,提出了一种通过分析仿生生物肌肉组织的机械性能获得运动策略的方法。数值仿真结果表明尺蠖生物运动能够满足机器人多自由度的变形运动,解决了运动策略问题,为仿生尺蠖移动机器人实现移动搜救功能提供运动控制理论基础。     

微小气动机器人系统的模糊自适应PID控制

基于尺蠖的移动机理,研制了一种具有柔性移动机构的微小气动机器人内窥镜诊疗系统。描述了微机器人系统的本体结构和运动机理,并通过分析机器人系统的驱动力学特性和机器人的移动控制特性,给出了基于模糊自适应PID的气压-位置伺服控制方法,计算机仿真实验结果表明基于模糊自适应PID算法可实现机器人系统的有效控制。     

呼吸参数监测机器人系统的气压伺服控制

本文研究了机器人移动状态的气压伺服控制,通过对人工筋驱动器进行压力控制实现机器人单步移动时的准位置伺服控制,研究了以气动人工筋驱动器和钳位气囊为控制对象的控制系统,建立控制阀的流量方程,研究了机器人气压（位置）的伺服控制算法,并进行计算机实验仿真分析和研究。     

微型仿生肠道内窥镜机器人的设计与实验

根据当前胃肠道内窥镜自主运动机器人的研究方向,设计了一种微型的肠道内窥镜机器人系统。机器人采用仿尺蠖式的运动步态,通过直流无刷电机驱动驻留-伸缩-驻留式的结构实现主动运动。整体采用模块化设计,主要包括驻留机构、伸缩机构、电路控制系统以及无线供能模块。对机器人结构模型进行了理论探讨,介绍了电路控制系统的设计,以及无线供能模块的构成。最终的机器人样机直径约为14 mm,整体长度约为61 mm。机器人在PVC柔性管道和猪小肠离体爬行实验中运行稳定可靠,能够实现前进、退后和停留等步态。实验结果表明该微型仿生肠道内窥镜机器人在肠道内可以实现主动运动。     

被动同心转向式多履带全向移动机器人设计

采用四组被动同心转向结构的履带单元,设计了一种多履带式全向移动机器人,该机器人不仅具有全向移动的能力,也具备运行平稳、载重能力强等特点。机器人使用ST Nucleo-F446RE开发板为控制器,采用旋转电位器测量每组履带单元的偏转角度,通过电机驱动器独立控制8个履带运动,从而实现机器人的全向移动。实验采集了各个履带的运动速度和每组履带单元的偏转角度,通过航位推测法计算机器人在两种运动中的轨迹,验证了机器人的全向移动能力。     

一种基于总线的移动探测机器人控制系统设计与实现

针对机械臂定位相关的控制算法缺乏合适验证平台的问题,将移动机器人技术和机械臂控制技术相结合,在分布式控制系统结构的基础上设计并实现了移动探测机器人原型样机。该系统由一个中央主控单元和多个从控制单元构成,单元之间通过总线相连,以实现探测机械臂各部分的模块化。该控制系统已经成功应用于实验室的探测机器人中。该设计能够完成对机械臂运动控制任务,可以用于移动探测机器人平台的建立以及相关算法的实现。     

四足仿生机器人单腿系统

为实现四足仿生机器人动步态行走,设计一款基于液压驱动方式的机器人仿生单腿系统.首先,在四足哺乳动物肌肉-骨骼结构分析的基础上,确定了机器人单腿的自由度配置;其次,通过机器人在平坦路面上的行走运动仿真,获得关节输出特性;随后,在仿真研究的基础上,完成了关节驱动机构设计、液压驱动器选型、4自由度单腿设计以及控制系统设计;最后,搭建单腿子系统性能测试平台,并完成了单腿纵向弹跳实验.弹跳实验验证了机械结构和控制系统设计的正确性和相关控制算法的有效性.     

Adaptive RBF neural network control of robot with actuator nonlinearities

In this paper, an adaptive neural network control scheme for robot manipulators with actuator nonlinearities is presented. The control scheme consists of an adaptive neural network controller and an actuator nonlinearities compensator. Since the actuator nonlinearities are usually included in the robot driving motor, a compensator using radial basis function (RBF) network is proposed to estimate the actuator nonlinearities and eliminate their effects. Subsequently, an adaptive neural network controller that neither requires the evaluation of inverse dynamical model nor the time-consuming training process is given. In addition, GL matrix and its product operator are introduced to help prove the stability of the closed control system. Considering the adaptive neural network controller and the RBF network compensator as the whole control scheme, the closed-loop system is proved to be uniformly ultimately bounded (UUB). The whole scheme provides a general procedure to control the robot manipulators with actuator nonlinearities. Simulation results verify the effectiveness of the designed scheme and the theoretical discussion.     

Nonsingular predefined-time dynamic surface control of a flexible-joint space robot with actuator constraints

To achieve predefined-time trajectory tracking control of a flexible-joint space robot(FJSR) with actuator constraints, a nonsingular predefined-time dynamic surface control scheme is developed. The input saturation caused by actuator constraints is addressed via the designed predefined-time anti-saturation compensator. On this basis, two different control laws are designed for such high-order nonlinear systems by utilizing the backstepping technique, and a novel nonlinear filter is constructed to filter the virtual control signals, thus avoiding the “differential expansion” phenomenon. Moreover, a singularity-free auxiliary function is designed to solve the singularity issue generated by the derivative of fractional power terms in the predefined-time control algorithm framework. The closed-loop system is proven to be semi-globally predefined-timely uniformly ultimately bounded (SGPTUUB) via constructing the suitable Lyapunov function. The difference and effectiveness of the two designed control laws are illustrated by the conducted simulations. Both of them allow the FJSR system to track the desired trajectory in a reasonably predefined time.     

电驱移动机器人多变量固定时间连续编队控制

针对扰动下电驱动非完整移动机器人固定时间编队控制问题,通过引入包含驱动器动力学的领航者-跟随者状态空间动力学模型,分两步对编队控制器进行了设计。对领航者跟随者编队运动学模型进行了多变量固定时间控制设计。在动力学层面,为实现扰动下的速度跟踪,通过辅助输入设计了一种跟随者机器人多变量超螺旋固定时间连续电压控制器。所提算法使机器人编队克服了跟随者机器人所受干扰,确保了跟随者机器人与领航者在固定时间达到期望队形,跟随者在固定时间内跟随期望速度,设计的连续控制消除了开关控制的抖振现象。通过参数设计提前给定系统收敛的固定时间,与系统初始状态无关。基于Lyapunov方法进行了系统稳定性分析。通过仿真对算法进行了验证。     

Adaptive robust fuzzy control for path tracking of a wheeled mobile robot

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

智能空气微生物采样机器人的设计与实现

在恶劣环境下人工采集空气中的微生物存在巨大的安全隐患,急需机器以自主作业方式取代人工方式.为此,该文设计并实现了一种智能空气微生物采样机器人,包括室内远程控制单元、气流控制单元、主机械手三维运动控制单元、手爪控制单元、刻字控制单元、电源管理单元、GPRS通信模块、安全监控模块、信息存储模块、电磁阀控制组、系统时钟模块、液晶触摸屏模块和轻型车载冰箱等.该机器人能全自动完成空气微生物的采样工作,系统功能全面、安全稳定、环境适应性强,能满足恶劣环境下长时间不间断工作的要求.     

Development of a remote control system for construction machinery for rescue activities with a pneumatic robot

Rescue activities at disaster sites often require the remote control of construction machinery to ensure the safety of the workers. A pneumatic 6-d.o.f. robot arm was developed to achieve the remote control of construction machinery. A lightweight fiber-knitted-type pneumatic artificial rubber muscle was selected as the actuator for the arm after considering portability and installation issues. A control system was then designed to remotely operate the pneumatic robot arms. The system consists of the slave and master side. The slave side is composed of two robot arms, a control box, a power generator and an air compressor. The master side consists of two joysticks and a laptop PC. A wireless LAN was employed to achieve the remote control. Construction machinery was retrofitted with the pneumatic robot and field tests were performed at a real construction site. The operation times using remote control and direct operation were compared. The results confirmed the effectiveness of the proposed system.     

Adaptive task-space regulation of rigid-link flexible-joint robots with uncertain kinematics

In this paper, an adaptive control scheme is proposed for the regulation problem of rigid-link flexible-joint (RLFJ) robots with uncertain kinematics. Existing research works in literature on RLFJ robot control assume exact knowledge of the kinematics of robot, and no result that can deal with kinematics uncertainty in RLFJ robot has been proposed so far. This paper presents the first study addressing this problem. The adaptive control scheme proposed can deal with the kinematics uncertainty and uncertainties in both link and actuator dynamics of the RLFJ robot system. A nonlinear observer is designed to avoid the use of acceleration due to the fourth-order overall dynamics. Asymptotic stability of the closed-loop system is shown and sufficient conditions are presented to guarantee the stability. Simulation results are provided to illustrate the effectiveness of the proposed control method.     

基于STM32的力反馈型康复机器人控制系统设计

研究了一种基于STM32的力反馈型康复机器人控制系统的设计。采用位置传感器和扭矩传感器检测康复机器人机械臂的位置信息以及机械臂与患者的相互作用力信息,将位置信息与作用力信息送入基于ARM-M3内核的STM32微控制器进行处理,从而实现康复机器人中驱动电机的控制。该系统硬件处理电路包括了扭矩信号的信号调理单元、微控制器控制单元、电机驱动单元以及USB接口单元。经实验验证,本系统可以实现康复机器人的平稳安全的控制。