基于证据理论的虚拟力机器人网络控制*

将网络与机器人相连,延伸网络的应用领域,可以实现价格低廉的远程监视与操作,而远程控制成功实现的关键在于信息的正确获得。利用Dempster-Shafer对六个超声波传感器所获取的距离信息进行融合,而后连同速度信息提供给弹簧-阻尼器系统以构建虚拟力;力的信息通过编程映射到游戏杆上,变成操纵方向的约束力。通过采用微软公司的带有力反馈的操纵杆作为力觉提示装置控制移动机器人在结构化环境下顺利运行,验证了虚拟力信息获取方法的有效性。     

基于Linux的游戏杆控制的实现方法

游戏杆作为一种输入设备,往往被人们用来玩电脑游戏。但是,在科学研究领域,游戏杆可以被用作人机交互的接口。一般来说,游戏杆具有三个自由度,因此可以用它来操 控被控对象在三雏空间中的运动。所以,如果实现对游戏杆的控制,那么就可以用游戏杆来控制被控对象的运动。本文主要介绍了两种游戏杆控制的实现方法。     

未知环境下基于Elman网络力控制的移动机器人避障研究

避障控制一直是移动机器人路径规划的难点.提出了一种未知环境下基于神经网络的机器人动态避障方法,同时把混合力/位置控制结构应用到移动机器人的避障控制中.力控制算法是通过在移动机器人和障碍物之间形成虚拟力场,并对其整定,以使它们两者之间能保持期望距离.由于移动机器人的动力学模型和障碍物的不确定性也会对避障控制的性能造成影响,因此采用Elman神经网络来补偿不确定性,同时整定移动机器人和障碍物之间的精确距离.仿真实验表明该动态避障算法是有效的.     

无线网络环境下移动机器人的控制策略研究

在移动机器人控制性能优化的研究中,针对无线控制网络中存在时延的情况,进行了控制器与补偿器的研究与设计.首先建立了移动机器人动力学模型,并针对模型设计离散反演控制器使移动机器人能够对给定信号进行跟踪.引入无线网络,进而分析网络时延对无线网络控制系统性能的影响,并针对网络时延利用预测控制算法设计控制序列预测补偿器,从而完成在时延存在的情况下仍然可以对移动机器人进行准确控制的无线移动机器人控制系统.仿真结果表明,设计的控制器与补偿器为无线网络环境下移动机器人的控制性能优化提供了参考.     

基于运动描述语言的轮式移动机器人控制

介绍了一种基于运动描述语言的轮式移动机器人控制方法．运动描述语言不仅可以有效地描述机器人系统中离散和连续动力学过程的相互作用，而且可以定量地描述操纵机器人的复杂性．利用该方法对具有非完整约束的轮式移动机器人的位姿镇定问题进行了研究，仿真结果验证了该方法的有效性．     

非时间参考的移动机器人路径跟踪控制

基于非时间参考的思想提出了一种移动机器人路径跟踪控制方法.首先选择移动机器人实际路径在某参考系下的x轴投影作为非时间参考量,并针对一类几何路径的跟踪建立移动机器人非时间参考的运动学模 型,据此设计以恒定速度跟踪期望路径的控制律,然后在此基础上给出跟踪任意几何路径的分段控制策略.此跟踪 控制系统所采用的参考量为非时间量􀁯,摆脱了时间因素的影响,因此能提高移动机器人在不确定环境中的跟踪能 力.仿真和物理实验表明了控制方法的有效性.􀁱     

基于虚拟现实技术的移动机器人视觉伺服控制系统设计

为了有效确保移动机器人视觉伺服控制效果,提高移动机器人视觉伺服控制精度,设计了基于虚拟现实技术的移动机器人视觉伺服控制系统。通过三维视觉传感器和立体显示器等虚拟环境的I/O设备、位姿传感器、视觉图像处理器以及伺服控制器元件,完成系统硬件设计。从运动学和动力学两个方面,搭建移动机器人数学模型,利用标定的视觉相机,生成移动机器人实时视觉图像,通过图像滤波、畸变校正等步骤,完成图像的预处理。利用视觉图像,构建移动机器人虚拟移动环境。在虚拟现实技术下,通过目标定位、路线生成、碰撞检测、路线调整等步骤,规划移动机器人行动路线,通过控制量的计算,实现视觉伺服控制功能。系统测试结果表明,所设计控制系统的位置控制误差较小,姿态角和移动速度控制误差仅为0.05°和0.12m/s,移动机器人碰撞次数较少,具有较好的移动机器人视觉伺服控制效果,能够有效提高移动机器人视觉伺服控制精度。     

基于模糊力控制算法的移动机器人避障控制

根据机器人的末端执行器和外界环境表面接触与移动机器人避障控制的相似点,将力/位置控制成功应用到移动机器人的避障控制领域内.对新颖的移动机器人避障控制算法是通过在移动机器人和障碍物之间形成虚拟力场,且对其进行整定以使两者之间能保持期望的距离.因为机器人动力学模型和障碍物的不确定性会对避障控制性能造成影响,为避免碰撞,采用模糊PD的智能混合力/位置控制来整定机器人和障碍物精确距离的力场.通过仿真研究证明了算法的有效性,可为机器人设计提出可靠依据.     

基于模糊控制的移动机器人避障研究

针对移动机器人在未知环境中的不确定性,利用Matlab构建了多传感器仿真试验移动平台,在Simulink中搭建移动机器人运动学模型,利用多传感器采集环境中的障碍物信息与目标物的方位角,设计了具有避障功能的模糊控制算法.通过模糊控制器控制移动机器人的左右轮速度实现机器人的转弯以及直走,根据机器人实时的角度反馈信息不断修正机器人的位姿以精确避障.仿真实验验证了该方法的可行性及有效性.     

找回经典街机的感觉手把手教你用Wii手柄玩Android游戏

Android设备上玩游戏,如果玩的是非触控游戏,像是射击游戏、动作游戏,通常都会有一个虚拟游戏杆浮现在屏幕上,然后让你用手指头在虚拟游戏杆上滑动,来控制飞机或是人物的动作.不过,通过触控屏幕来控制游戏杆的手感真的很糟,与实际游戏杆比较起来天差地远,而且手机屏幕小,游戏杆缩在那么小的屏幕上,其实很容易因为手指头滑动的一个错失,就错失了攻击的最佳良机.     

Human-robot cooperation control for installing heavy construction materials

Previously, ASCI (Automation System for Curtain-wall Installation) which combined with a multi-DOF manipulator to a mini-excavator was developed and applied on construction site. As result, the operation by one operator and more intuitive operation method are proposed to improve ASCI's operation method which need one person with a remote joystick and another operating an excavator. The human-robot cooperative system can cope with various and untypical constructing environment through the real-time interacting with a human, robot and constructing environment simultaneously. The physical power of a robot system helps a human to handle heavy construction materials with relatively scaled-down load. Also, a human can feel and response the force reflected from robot end effecter acting with working environment. This paper presents the feasibility study regarding the application of the proposed human-robot cooperation control for construction robot through experiments on a 2DOF manipulator.     

Construction of an Omnidirectional Mobile Robot Platform Based on Active Dual-Wheel Caster Mechanisms and Development of a Control Simulator

In this paper, we describe a new type of holonomic and omnidirectional mobile robot using two driving assemblies, one of which consists of two independent driving wheel mechanisms, just like an active dual-wheel caster with an offset steered axis. Kinematic models of the wheel mechanism and a mobile robot with two driving assemblies are derived, and these models are applied to construct a feedback control system based on a resolved velocity control system for the robot. The effectiveness of the presented method is illustrated by some computer simulations. The prototype of a mobile robot platform using two driving assemblies, which can be controlled by a personal computer or a 3D joystick manipulated by human, is constructed.     

VFF^＋：改进的虚拟力场移动机器人避障算法

分析了虚拟力场法采用全局栅格表示环境信息具有累积误差大、信息存储量大的缺点，设计了动态栅格法表示环境信息，使用跟随机器人移动的扇形栅格表示环境信息，使用栅格中心坐标投影的方法存储多次超声测量数据信息，与势场法相结合对机器人进行导航控制。经仿真和实验验证，改进后的虚拟力场法取得了良好的应用效果。     

遥操作机器人的新型力反馈算法*

在采用液压挖掘机改造的遥操作机器人双向伺服控制系统中,针对大臂和前臂两个自由度构建力反馈控制算法。以准确地获取从端机器人与环境的作用力,使反馈力能够更好地反映从端工作状况为目的,采用构建干扰力补偿项的方法消除干扰力对反馈力的影响;以机器人转角为输入,以空载时检测到的液压缸作用力为输出,通过径向基函数构建干扰力补偿项,此补偿项可对多种因机器人的机械本体动力学特性产生的干扰力之合力进行补偿。实验证明,在以液压机构为从手的双向力反馈系统中,通过构建干扰力补偿项的方法提高力反馈效果的方法是可行的,采用的带有干扰力     

Stabilization of robot motion and contact force interaction for third-order motor dynamics

An approach to the synthesis of control laws stabilizing motion and force in contact tasks, based on the exponential stability of the closed-loop control system, is described. When using the synthesized control laws, simultaneous stabilization of both motion and force is achieved with a preset quality of the transient responses. The task is solved in a most general form, taking into account the constraints on robot control, its position and the force of interaction of the robot and the environment, and the external perturbations and inaccuracies of the measuring sensors, when the environment dynamics is being described by nonlinear second-order differential equation, and the robot dynamics includes the third-order equations of the robot actuators dynamics.     

自适应模糊与CMAC并行的机器人力/位置控制

为提高机器人系统对机器人末端操纵器与外界工作环境接触时，其接触刚度不确定性的自适应能力，在机器人力／位置混合控制的基础上，设计出了一种基于自适应模糊与CMAC并行控制的机器人力控制器，采用小脑模型神经控制器实现前馈控制，实现被控对象的逆动态模型，自适应模糊控制器实现反馈控制，保证系统的稳定性，且抑制扰动。以平面两关节机器人进行仿真，仿真结果表明，系统的自适应能力和力跟踪能力有显著的提高，机械手在其末端操纵器与刚性变化范围较大的外界工作环境接触时，具有较强的适应能力，较好地完成了机器人的力／位置控制。     

Neural network-based Smith predictor design for the time-delay in a tele-operated control system

This article presents a methodology for compensating for the time-delay effects in tele-operated control systems. Compensation can be carried out by a neural network. A tele-operated system consists of a master robot to give commands, and a slave robot to work with the environment. The positional command by the master robot is transferred to the slave robot, and the contact force from the environment is transferred back to the master robot. The structure of the Smith predictor is modified by replacing the linear estimator with a neural network whose structure is based on the radial basis function (RBF). The RBF network identifies the slave model to deal with the nonlinearities in the system. Simulation studies have been conducted, and experimental studies of one-directional force control were performed to confirm the simulation results.     

Usability Evaluation of VR Interface for Mobile Robot Teleoperation

This article presents the results from research in which 3 different remote control interfaces were compared to assess the impact of interface structure on the performance of the operator for remotely controlled mobile inspection robots. The primary control interface of a mobile robot consists of a head-mounted display, data gloves for gripper control, joystick for movement control of the robot platform, and a motion tracking system for measuring head orientation and hand position. In order to compare different control interfaces, an additional system, based on a Liquid Crystal Display monitor and joystick, was prepared. Results of this study show that the use of virtual reality techniques in the interfaces of mobile inspection robots increases operator productivity, the level of spatial presence, and distance evaluation while facilitating the execution of tasks, as well as improving and speeding up their execution and reducing the operator’s time needed to adapt to the control interface. The latter is achieved with the increased level of intuitive control while ensuring comfort.     

Remote control of space robots

A method for the remote control of a space robot is proposed for the case of large delays in the transmission of control signals from the Earth to the local robot control system and in feedback signals. The method involves the use of the model of the space robot and its current environment with the simulation of gravity conditions at the ground control center. In this model environment, the operator should carry out the required actions by controlling the space robot model in the master-slave mode using an arm with six degrees of freedom capable of reflecting the interaction force of a model robot working tool with models of the objects of the environment. The arm movement trajectory and the law of time variation of the reflected interaction force vector are program-based for the local space robot control system and should be executed by it upon reception from the ground control center. The robot’s possible erroneous actions generated by the inevitable inaccuracy of the environment model are compensated by the proposed method of programmed trajectory correction. In accordance with it, in order to generate correction signals, additional information received from different sensors is used. These sensors can be installed on both the model and space robot itself. This information includes data on the mutual position of a robot’s working tool and models of the objects of the environment, as well as on the interaction forces between them. The paper presents a detailed theoretical justification of the proposed approach and experimental results that confirm the theoretical conclusions.