基于视觉模型成像的六轴焊接机器人关节运动姿态规划研究

由于传统的六轴焊接机器人关节运动姿态规划方法存在关节运动姿态规划精度低、规划时间长的问题,提出基于视觉模型成像的六轴焊接机器人关节运动姿态规划方法.计算摄像机与机器人坐标关系,并通过图像雅克比矩阵,确定图像特征与机器人关系,在工作空间内把直线的始点与终点轨迹离散化,完成坐标转换,获取每个关节角度值,通过围绕焊接机器人各轴角度值确定欧拉角3个变量,利用欧拉角进行姿态规划,实现六轴焊接机器人关节运动姿态规划.实验结果表明,所提方法的六轴焊接机器人关节运动姿态规划精度较高,规划时间较短.     

机器人操作臂跟踪动态目标的轨迹规划方法

针对机器人操作臂跟踪运动目标问题,提出一种基于遗传算法的轨迹规划方法。通过对关节加速度的增量进行编码,实现在操作臂的关节空间进行轨迹优化,得到操作臂在跟踪运动目标过程中所需要的轨迹。仿真计算的结果表明,所提出的方法是有效的。     

欠驱动冗余度空间机器人优化控制

欠驱动控制是空间技术中容错技术的重要方面.本文研究了被动关节中有制动器的欠驱动冗余度空间机器人系统的运动优化控制问题.从系统动力学方程出发,分析了欠驱动冗余度空间机器人的优化能力和控制方法;给出了主、被动关节间的耦合度指标;提出了欠驱动冗余度空间机器人系统的“虚拟模型引导控制”方法,在这种方法中采用与欠驱动机器人机构等价的全驱动机器人作为模型来规划机器人的运动,使欠驱动系统在关节空间中逼近给出的规划轨迹,实现了机器人末端运动的连续轨迹运动优化控制;通过末关节为被动关节的平面三连杆机器人进行了仿真,仿真的结果证明了提出算法的有效性.     

基于深度相机的移动机器人视觉跟踪控制研究

基于视觉利用移动机器人进行运动目标跟踪,该文提出一种基于二自由度云台和RGB-D相机的运动目标视觉跟踪及移动机器人路径实时规划、跟踪方法。该方法利用核相关滤波算法在图像中实时追踪目标,控制二自由度云台使深度相机实时对准目标,并根据深度相机得到目标的深度信息,利用坐标转换得到目标相对于机器人的位置信息;其后移动机器人根据目标的位置信息,基于五次多项式进行路径规划;最后采用李雅普诺夫控制律对移动机器人进行轨迹跟踪控制,使得机器人能够平稳地跟踪目标运动。该算法在阿克曼移动机器人上进行了实验,实验结果验证了算法的有效性和实时性。     

基于最优化线性搜索的稳定步态规划方法

提出一种基于最优化线性搜索的方法规划人形机器人的步态.通过对脚踝关节末端轨迹运动的规划和参考零力矩点(ZMP:zero moment point)轨迹的规划,将最优化泛函极值问题转换成为基于非线性约束最优化的问题,将连续空间多变量规划问题转换成为离散空间二维变量规划问题,提出了一套能够在线规划步态的控制算法.该算法的收敛性和稳定性在仿真和实物上都得到了验证.     

空间机器人目标捕获的自适应规划

与地面固定基座机器人不同的是,空间机器人的运动学方程中含有动力学参数。在执行目标捕获任务时,目标动力学参数的不精确会给空间机器人的规划带来致命的影响。针对目标捕获后动力学参数不精确情况下的关节空间规划问题,在建立了自由飘浮空间机器人运动学模型的基础上,给出了雅可比矩阵及其动量守恒方程中的惯性参数以及惯性参数的组合参数线性化的具体形式,提出了一种关节空间的自适应规划方法。以平面二连杆空间机器人为研究对象进行仿真验证。结果表明,所提出的自适应规划方法可以有效降低惯性参数不精确给运动规划带来的影响,为空间机器人执行目标捕获等任务时提供了任务空间内精确轨迹跟踪的能力。     

场景摄像机构型下图像空间内的无标定路径规划研究

基于图像的视觉伺服可用于对机械臂的运动进行有效的控制。然而,正如许多研究者指出的,当初始位置和期望位置相距较远时,此种控制策略将因其局部特性而存在收敛性、稳定性问题。通过在图像平面内定义充分的图像特征轨迹,并对这些轨迹进行跟踪,我们可以充分利用基于图像的视觉伺服所固有的局部收敛性及稳定性特性这一优势,从而避免初始位置与期望位置相距较远时所面临的问题。因此,近年来,图像空间路径规划已成为机器人领域的一个热点研究问题。但是,目前几乎所有的有关结果均是针对手眼视觉系统提出的。本文将针对场景摄像机视觉系统提出一种未标定视觉路径规划算法。此算法在射影空间中直接计算图像特征的轨迹,这样可保证它们与刚体运动一致。通过将旋转及平移运动的射影表示分解为规范化形式,我们可以很容易地对其射影空间内的路径进行插值。在此之后,图像平面中的图像特征轨迹可通过射影路径产生。通过这种方式,此算法并不需要特征点结构和摄像机内部参数的有关知识。为了验证所提算法的可行性及系统性能,本文最后给出了基于PUMA560机械臂的仿真研究结果。     

基于主从任务转化的冗余度机器人避障算法

在冗余度机器人的避障规划问题中,当障碍影响机器人末端运动时,避障运动和机器人的末端轨迹跟踪运动会发生相互冲突.针对这个问题,提出了基于主从任务转化的避障算法.该方法将避障运动的操作空间定义为1维的运动空间,引入了2个转换变量,可以根据得到的实时最小距离的变化,实现机器人末端的轨迹跟踪运动和避障运动之间光滑连续的优先级转换.最后,通过对一个3自由度平面机器人的仿真实验,对算法的正确性进行了验证.结果表明,机器人与障碍物的最近距离大于0.02m,并且机器人末端可以准确地到达目标位置.所提出的方法不仅能实现冗余度机器人的避障,而且能防止任务之间的冲突.     

空间机器人捕获运动目标的协调规划与控制方法

针对目标以任意轨迹运动且其轨迹可能与``有保证工作空间'不相交的问题, 提出了空间机器人捕获运动目标的协调规划与控制方法. 首先, 根据手眼视觉测量数据, 预测目标的运动路径, 由此确定空间机器人对目标的最优交会姿态及最佳捕获臂型; 其次, 规划基座姿态及机械臂关节角的轨迹; 最后, 采用协调控制的方法, 实现空间机器人系统对运动目标的最优捕获(以最优交会姿态及最佳捕获臂型对目标进行捕获). 仿真结果表明了该方法的有效性.     

曲线识别技术在机器人中的应用

以VC 作为开发工具,运用开源的计算机视觉库OpenCv,采集图像信息,进行图像处理,得到轨迹曲线的数据,控制实验室UP6机器人,使机器人手部跟踪曲线的轨迹运动。在工业自动化上有一定的价值。     

基于干扰观测器的机械臂广义模型预测轨迹跟踪控制

为实现对多自由度机械臂关节运动精确轨迹跟踪,提出一种基于非线性干扰观测器的广义模型预测轨迹跟踪控制方法。针对机械臂轨迹跟踪运动学子系统,采用广义预测控制（Generalized Predictive Control,GPC）方法设计期望的虚拟关节角速度。对于机械臂轨迹跟踪动力学子系统,考虑机械臂的参数不确定性和未知外界扰动,利用GPC方法设计关节力矩控制输入,基于非线性干扰观测器方法实时估计和补偿系统模型中的不确定性。在李雅普诺夫稳定性理论框架下证明了机械臂关节角位置和角速度的跟踪误差最终收敛于零的小邻域。数值仿真验证了所提出控制方法的有效性和优越性。     

基于结构光的机器人弧焊混合视觉伺服控制

A novel hybrid visual servoing control method based on structured light vision is proposed for robotic arc welding with a general six degrees of freedom robot. It consists of a position control inner-loop in Cartesian space and two outer-loops. One is position-based visual control in Cartesian space for moving in the direction of weld seam, i.e., weld seam tracking, another is image-based visual control in image space for adjustment to eliminate the errors in the process of tracking. A new Jacobian matrix from image space of the feature point on structured light stripe to Cartesian space is provided for differential movement of the end-effector. The control system model is simplified and its stability is discussed. An experiment of arc welding protected by gas CO_2 for verifying is well conducted.     

Direct visual tracking control of remote cellular robots

This paper presents the design of a stable non-linear control system for the remote visual tracking of cellular robots. The robots are controlled through visual feedback based on the processing of the image captured by a fixed video camera observing the workspace. The control algorithm is based only on measurements on the image plane of the visual camera–direct visual control–thus avoiding the problems related to camera calibration. In addition, the camera plane may have any (unknown) orientation with respect to the robot workspace. The controller uses an on-line estimation of the image Jacobians. Considering the Jacobians’ estimation errors, the control system is capable of tracking a reference point moving on the image plane–defining the reference trajectory–with an ultimately bounded error. An obstacle avoidance strategy is also developed in the same context, based on the visual impedance concept. Experimental results show the performance of the overall control system.     

基于神经网络的机器人手眼无标定平面视觉跟踪

在手眼关系及摄像机模型完全未知的情况下,建立了眼在手上机器人平面视觉跟踪 问题的非线性视觉映射模型,将图像特征空间和机器人工作空间紧密地联系起来.在此基础 上,设计了基于人工神经网络的视觉跟踪控制方案,将视觉跟踪问题转化为图像特征空间中 的定位问题.仿真结果表明该算法能完全消除稳态跟踪误差,具有很强的环境适应性和容错 能力,算法简单,易于实时实现.     

Vision-Based Robotic Motion Control for Non-autonomous Environment

A visual servo control system with SOPC structure is implemented on a retrofitted Mitsubishi Movemaster RV-M2 robotic system. The hardware circuit has the functions of quadrature encoder decoding, limit switch detecting, pulse width modulation (PWM) generating and CMOS image signal capturing. The software embedded in Nios II micro processor has the functions of using UART to communicate with PC, robotic inverse kinematics calculation, robotic motion control schemes, digital image processing and gobang game AI algorithms. The digital hardware circuits are designed by using Verilog language, and programs in Nios II micro processor are coded with C language. An Altera Statrix II EP2S60F672C5Es FPGA chip is adopted as the main CPU of the development board. A CMOS color image sensor with 356 ×292 pixels resolution is selected to catch the environment time-varying change for robotic vision-based servo control. The system performance is evaluated by experimental tests. A gobang game is planned to reveal the visual servo robotic motion control objective in non-autonomous environment. Here, a model-free intelligent self-organizing fuzzy control strategy is employed to design the robotic joint controller. A vision based trajectory planning algorithm is designed to calculate the desired angular positions or trajectory on-line of each robotic joint. The experimental results show that this visual servo control robot has reliable control actions.     

State Space Constrained Iterative Learning Control for Robotic Manipulators

Real‐life work operations of industrial robotic manipulators are performed within a constrained state space. Such operations most often require accurate planning and tracking a desired trajectory, where all the characteristics of the dynamic model are taken into consideration. This paper presents a general method and an efficient computational procedure for path planning with respect to state space constraints. Given a dynamic model of a robotic manipulator, the proposed solution takes into consideration the influence of all imprecisely measured model parameters, making use of iterative learning control (ILC). A major advantage of this solution is that it resolves the well‐known problem of interrupting the learning procedure due to a high transient tracking error or when the desired trajectory is planned closely to the state space boundaries. The numerical procedure elaborated here computes the robot arm motion to accurately track a desired trajectory in a constrained state space taking into consideration all the dynamic characteristics that influence the motion. Simulation results with a typical industrial robot arm demonstrate the robustness of the numerical procedure. In particular, the results extend the applicability of ILC in robot motion control and provide a means for improving the overall trajectory tracking performance of most robotic systems.     

Parametric Planning for Multiple Cooperative Robots

A novel planning strategy, parametric planning, is proposed to negotiate the task-oriented object manipulation of multiple coordinated robots. The approach provides an advantage to improve flexibility of robotic cooperation, in which the desired trajectories in Cartesian space derived from task requirements are converted into the trajectories of robots in joint space for a fixed-coordinated multi-robot system. For this purpose, a parametric cooperative index matrix is introduced to handle the relationship of the input desired Cartesian trajectories and the position of robots. A case study of 2-dimension object-motion trajectory tracking using four robots is presented in the end. It proved that the proposed approach effectively delivers trajectory task requirements to the joint trajectories of robots.     

Time-optimal and jerk-continuous trajectory planning for robot manipulators with kinematic constraints

In this paper a high smooth trajectory planning method is presented to improve the practical performance of tracking control for robot manipulators. The strategy is designed as a combination of the planning with multi-degree splines in Cartesian space and multi-degree B-splines in joint space. Following implementation, under the premise of precisely passing the via-points required, the cubic spline is used in Cartesian space planning to make either the velocities or the accelerations at the initial and ending moments controllable for the end effector. While the septuple B-spline is applied in joint space planning to make the velocities, accelerations and jerks bounded and continuous, with the initial and ending values of them configurable. In the meantime, minimum-time optimization problem is also discussed. Experimental results show that, the proposed approach is an effective solution to trajectory planning, with ensuring a both smooth and efficiency tracking performance with fluent movement for the robot manipulators.     

无人车辆轨迹规划与跟踪控制的统一建模方法

无人车辆的轨迹规划与跟踪控制是实现自动驾驶的关键.轨迹规划与跟踪控制一般分为两个部分，即先根据车辆周边环境信息以及自车运动状态信息规划出参考轨迹，再依此轨迹来调节车辆纵横向输出以实现跟随控制.本文通过对无人车辆的轨迹规划与跟踪进行统一建模，基于行车环境势场建模与车辆动力学建模，利用模型预测控制中的优化算法来选择人工势场定义下的局部轨迹，生成最优的参考轨迹，并在实现轨迹规划的同时进行跟踪控制.通过CarSim与MATLAB/Simulink的联合仿真实验表明，该方法可在多种场景下实现无人车辆的动态避障.