真空并联机器人轨迹规划仿真

为了实现FROG-LEG型真空并联机器人准确经过多个中间位姿点的路径规划,研究了类机器人NURBS曲线路径规划的关键问题.通过建立FROG-LEG型并联机器人等效的串联运动学模型,获得了机器人运动学的正反解,在运动学基础上设计了该类机器人基于NURBS曲线的路径规划方案.通过Matlab的robot tool工具箱,进行了FROG-LEG型真空并联机器人运动学和路径规划的仿真.仿真结果证明,路径规划方案可以很好的让机器人通过中间插补位姿.从而从理论上解决了FROG-LEG型真空并联机器人路径规划中需要精确经过多个插补位姿的难题,并为实现FROG-LEG型真空并联机器人采用NURBS曲线轨迹规划提供理论依据.     

基于末端转角误差的并联机器人零点标定方法

针对一种4自由度高速并联机器人（Cross-IV机器人）的零点标定问题,提出了一种基于末端转角误差信息的快速零点标定方法．基于机器人的单支链闭环矢量方程,建立了零点误差全集与末端误差之间的映射模型．通过对误差传递矩阵的分解,在仅利用旋转编码器对末端转角误差进行测量的基础上,构建了该机器人的快速零点误差辨识模型．为进一步最大化测量效率及提高辨识矩阵的鲁棒性,提出了一种优化的测量点选择方案．通过仿真详细验证了该零点标定方法的鲁棒性与准确性．基于激光跟踪仪的验证实验表明,经标定后机器人末端位置误差降低至1.312 mm,转角误差降低至0.202°,标定结果表明该零点标定方法简单、有效．     

软体机器人手眼视觉/形状混合控制

当末端带有相机的连续型软体机器人进行作业时,由于避障、安全性等多方面因素,既需要末端相机－机器人系统的视觉伺服,也需要机器人的整体形状控制．针对这个问题,本文提出了一种软体机器人手眼视觉/形状混合控制方法．该方法无需知道空间特征点的3维坐标,只需给定特征点在末端相机像平面的期望像素坐标和软体机器人的期望形状就可达到控制目的．建立了软体机器人的运动学模型,利用该模型,结合深度无关交互矩阵自适应手眼视觉控制和软体机器人形状控制,提出了一种混合控制律,并用李亚普诺夫稳定性理论对该控制律进行证明．仿真和实验的结果均表明,末端相机特征点像素坐标和形状可以收敛到期望值．     

基于相对坐标的机器人末端位姿测量方法

为了解决机器人末端6维位姿难以测量的问题,提出了一种末端位姿的间接测量方法,并给出了适用条件．该方法只需测量末端平台6个目标点在单方向上的相对位移,便可得到机器人末端的6维位姿数据,而且可以消除测量工具的零值系统误差．分析了各几何误差对测量精度的影响,得到了误差影响矩阵以指导测量精度补偿．最后,以一台6自由度运动模拟器为例验证了该方法的有效性．     

一种笛卡儿空间的自由漂浮空间机器人路径规划方法

针对自由漂浮空间机器人工作时需保证载体姿态稳定的问题,提出了一种笛卡儿空间内载体姿态无扰的自由漂浮空间机器人非完整路径规划方法．首先,基于自由漂浮空间机器人特征方程和角动量守恒方程得到广义雅可比矩阵;其次,出于路径规划的需要,分析了载体姿态无扰的自由漂浮空间机器人可达工作空间;最后,引入相关系数,设计了笛卡儿空间内的无扰向量合成算法．仿真得到的路径规划结果表明机械臂末端达到目标点的同时确保了载体姿态无扰动,从而验证了所提方法的可行性和有效性．     

一种多移动机器人的分布式滚动路径规划算法

本文研究了全局未知静态环境下多机器人路径规划问题，使用基于滚动窗口的机器人路径规划方法对机器人进行局部路径规划．并根据一定的规则在机器人之间进行路径的协调。仿真结果验证了算法的有效性。     

自由漂浮空间机器人避奇异规划—跟踪算法

针对路径相关空间内自由漂浮空间机器人无法进行有效跟踪控制的问题,设计了一种避奇异轨迹规划—跟踪算法,用于完成路径相关空间机械臂末端轨迹跟踪控制的任务．首先,分析奇异条件并设定安全边界曲线,求解回避奇异的基座姿态角阈值,从而得到避奇异参考轨迹及初始状态值．接着,利用自由漂浮空间机器人非线性动力学模型具有状态依赖参数的类线性结构特点,基于状态依赖Riccati方程设计跟踪控制器对末端速度进行跟踪,保证闭环系统的局部渐近稳定性．所提方法克服了传统方法将工作空间约束在路径无关空间的缺点．仿真结果表明,该算法具有比比例微分（proportional derivative,PD）控制更高的跟踪精度．同时,在存在输入干扰的情况下仍然能够实现有效跟踪．     

基于示教与视觉纠偏的机器人自动焊接方法研究

给出了一种示教与纠偏相结合的焊缝跟踪方法,用于实现机器人的自动焊接．针对传统的示教再现机器人,由激光视觉传感器测量实际路径与示教路径之间的偏差．机器人控制器根据示教路径和偏差,对焊枪的运动方向和位置进行调整,实现焊缝跟踪．利用六自由度机器人和激光结构光视觉传感器设计了实验系统,对所提方法进行了实验．实验结果验证了该方法的有效性．     

电缆虚拟布线及其逆运动学仿真

在产品虚拟样机中利用人机交互方法进行电缆路径规划,得到一个基于NURBS曲线的电缆几何模型,然后利用“蛇形机器人”方法建立电缆的物理模型,基于逆运动学原理计算其弯曲角度.     

基于云模型的机器人自主乘梯控制方法研究

为了实现机器人在无人协助时完成乘梯操作,提出了机器人自主乘梯控制方法。首先建立了机器人乘梯过程的有限状态机模型,然后介绍了基于数据融合理论的多传感器融合定位方法和基于颜色识别技术的机械臂末端位置调整方法,最后提出了有次序目标点路径规划方法及基于云模型的机器人路径跟踪方法。实验表明,所提出控制方法能够保证机器人准确完成乘梯过程,且具有较好的实用性和有效性。     

Development and implementation of a NURBS curve motion interpolator

This paper deals with the issues of development and implementation of a real-time NURBS interpolator for a six-axis robot. Using an open-architecture controller system as a testbed, a real-time NURBS curve interpolator was developed, implemented and tested. Sample runs were conducted with the resulting trajectories measured in real-time during robot motion. The resulting trajectories are analyzed, discussed and compared with those from a commonly used point-to-point approximation technique. The real-time NURBS curve interpolator's feasibility, advantages and related issues are also discussed.     

An adaptive parametric interpolator for trajectory planning

A real-time interpolation algorithm for trajectory planning is studied in this paper. The NURBS interpolation algorithm is proposed to confine contour errors and feedrate fluctuations. The feedrate is adjusted adaptively according to the specified acceleration/deceleration values and jerk value. A direct digital convolution method is also introduced into velocity planning for NURBS interpolator, and it is more efficient than the traditional method of polynomial functions. The feedrate at the sharp corner is smoothed by imposing limitations on the acceleration and jerk values generated in the machining process. Since the computation of the total length of NURBS curve is required for the digital convolution method, a numerical adaptive quadrature algorithm is used to approximate the integrand. Simulation results demonstrate the effectiveness of the proposed interpolator for machining curved paths.     

Redundant robot control using task based performance measures

The joint velocities required to move the end-effector of a redundant robot with a desired linear and angular velocity depend on its configuration. Similarly, the joint torques produced due to the force and moment at the end-effector also depend on its configuration. When the robot is near a singular configuration, the joint velocities required to attain the end-effector velocity in certain directions are extremely high. Similarly, in some configurations the joint torque produced at certain joints may be high for a relatively small magnitude of external force. An infinite number of trajectories in the joint space can be used to achieve a desired end-effector trajectory for redundant robots. However, a joint trajectory resulting in robot configurations requiring lower joint velocities or joint torques is desired. This may be achieved through a proper utilization of redundancy. Local performance measures for redundant robots are defined in this article as indicators of their ability to follow a desired end-effector trajectory and their ability to apply desired forces at the end-effector. Thus, these performance measures depend on the task to be performed. Control algorithms which can be efficiently applied to redundant robots to improve these performance measures are presented. These control algorithms are based on the gradient projection method. Gradients of the performance measures used in the control schemes result in simple symbolic expressions for “real world” robots'. Feasibility and effectiveness of these control schemes is demonstrated through the simulation of a seven-degree-of-freedom redundant robot derived from the PUMA geometry.     

Adaptive control of redundant multiple robots in cooperative motion

A redundant robot has more degrees of freedom than what is needed to uniquely position the robot end-effector. In practical applications the extra degrees of freedom increase the orientation and reach of the robot. Also the load carrying capacity of a single robot can be increased by cooperative manipulation of the load by two or more robots. In this paper, we develop an adaptive control scheme for kinematically redundant multiple robots in cooperative motion.In a usual robotic task, only the end-effector position trajectory is specified. The joint position trajectory will therefore be unknown for a redundant multi-robot system and it must be selected from a self-motion manifold for a specified end-effector or load motion. In this paper, it is shown that the adaptive control of cooperative multiple redundant robots can be addressed as a reference velocity tracking problem in the joint space. A stable adaptive velocity control law is derived. This controller ensures the bounded estimation of the unknown dynamic parameters of the robots and the load, the exponential convergence to zero of the velocity tracking errors, and the boundedness of the internal forces. The individual robot joint motions are shown to be stable by decomposing the joint coordinates into two variables, one which is homeomorphic to the load coordinates, the other to the coordinates of the self-motion manifold. The dynamics on the self-motion manifold are directly shown to be related to the concept of zero-dynamics. It is shown that if the reference joint trajectory is selected to optimize a certain type of objective functions, then stable dynamics on the self-motion manifold result. The overall stability of the joint positions is established from the stability of two cascaded dynamic systems involving the two decomposed coordinates.     

Adaptive position/force control of robot manipulators withoutvelocity measurements: theory and experimentation

In this paper, we design an adaptive position/force controller for robot manipulators during constrained motion. The proposed controller can compensate for parametric uncertainty while only requiring measurements of link position and end-effector force. A filtering technique is utilized to produce a pseudo-velocity error signal and thus, eliminate the need for link velocity measurements. The control strategy provides semiglobal asymptotic tracking performance for the end-effector position and the interaction force between the constraint and the end-effector. An experimental implementation of the proposed controller on a two-link planar robot is also presented.     

关节型机器人的似人操作构型规划

对关节型机器人的操作构型进行规划时,本文提出了一种新的规划方法,它结合了似人评估准则和机器人传速特性优化的概念,可实现有最大末端传速特性的操作,同时与人类手臂操作的特点最为相似.该方法首先利用应用人体工程学中的快速上肢评价准则(RULA)对机器人的操作空间进行划分,然后在各子空间内最大化机器人末端沿指定方向的传速速率.最终选定一个最符合人类操作特性又同时满足操作任务的机器人操作构型.通过在2自由度平面机器人和7自由度拟人机械臂上的规划实验进一步展示了本方法的使用,规划结果验证了其有效性.     

Maximum DLCC of Spatial Cable Robot for a Predefined Trajectory Within the Workspace Using Closed Loop Optimal Control Approach

One of the most important applications of cable robots is load carrying along a specific path. Control procedure of cable robots is more challenging compared to linkage robots since cables can’t afford pressure. Meanwhile carrying the heaviest possible payload for this kind of robots is desired. In this paper a nonlinear optimal control is proposed in order to control the end-effector within a predefined trajectory while the highest Dynamic Load Carrying Capacity (DLCC) can be carried. This purpose is met by applying optimum torque distribution among the motors with acceptable tracking accuracy. Besides, other algorithms are applied to make sure that the allowable workspace constraint is also satisfied. Since the dynamics of the robot is nonlinear, feedback linearization approach is employed in order to control the end-effector on its desirable path in a closed loop way while Linear Quadratic Regulator (LOR) method is used in order to optimize its controlling gains since the state space is linearized by the feedback linearization. The proposed algorithm is supported by doing some simulation studies on a two Degrees of Freedom (DOF) constrained planar cable robot as well as a six DOFs under constrained cable suspended robot and their DLCCs are calculated by satisfying the motor torque, tracking error and allowable workspace constraints. The results including the angular velocity, motors’ torque, actual tracking of the end-effector and the DLCC of the robot are calculated and verified using experimental tests done on the cable robot. Comparison of the results of open loop simulation results, closed loop simulation results and experimental tests, shows that the results are improved by applying the proposed algorithm. This is the result of tuning the motors’ torque and accuracy in a way that the highest DLCC can be achieved.     

Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

In this paper, we present a novel data-driven design method for the human-robot interaction (HRI) system, where a given task is achieved by cooperation between the human and the robot. The presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller design. The task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop, while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the inner-loop. Data-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance parameters. In the inner-loop, a velocity-free filter is designed to avoid the requirement of end-effector velocity measurement. On this basis, an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task space. The simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.      

基于立体视觉的机械手未知平面内曲线跟踪

为了提高机械手应用的灵活性,增强机械手对动态环境的适应能力,降低机械手对工件位置的依赖性,采用立体视觉技术对未知平面的法线方向进行估计,根据工程应用中对末端执行器的速度以及位姿的实际要求,采用PID控制策略控制机械手末端执行器与工件之间的相对位姿.进行了仿真实验以验证所提方法的有效性,结果表明:该方法能够实现末端执行器和工件之间相对位姿的动态控制.     

Kinematic calibration for collaborative robots on a mobile platform using motion capture system

For modern robotic applications that go beyond the typical industrial environment, absolute accuracy is one of the key properties that make this possible. There are several approaches in the literature to improve robot accuracy for a typical industrial robot mounted on a fixed frame. In contrast, there is no method to improve robot accuracy when the robot is mounted on a mobile base, which is typical for collaborative robots. Therefore, in this work, we proposed and analyzed two approaches to improve the absolute accuracy of the robot mounted on a mobile platform using an optical measurement system. The first approach is based on geometric operations used to calculate the rotation axes of each joint. This approach identifies all rotational axes, which allows the calculation of the Denavit–Hartenberg (DH) parameters and thus the complete kinematic model, including the position and orientation errors of the robot end-effector and the robot base. The second approach to parameter estimation is based on optimization using a set of joint positions and end-effector poses to find the optimal DH parameters. Since the robot is mounted on a mobile base that is not fixed, an optical measurement system was used to dynamically and simultaneously measure the position of the robot base and the end-effector. The performance of the two proposed methods was analyzed and validated on a 7-DoF Franka Emika Panda robot mounted on a mobile platform PAL Tiago-base. The results show a significant improvement in absolute accuracy for both proposed approaches. By using the proposed approach with the optical measurement system, we can easily automate the estimation of robot kinematic parameters with the aim of improving absolute accuracy, especially in applications that require high positioning accuracy.