基于特征识别的汽车复杂零件自校正检测系统

为了解决复杂零件在自动化装配过程中位置偏差与位姿偏角造成的装配问题,实现具有反馈调整能力的机械臂扫描控制,设计了基于激光三维扫描的实时检测系统。系统通过光栅扫描方式获取零件的三维面形数据,并利用边缘特征识别完成零件匹配,最终达到在工装环境下自动调整位置与位姿的目的。实验对SP165型机械臂进行控制,以6自由度参数作为检测精度的评价指标,分别对基于零件数模的仿真数据、固定扫描路径测试数据和自动调整扫描路径测试数据进行对比分析。结果显示,采用本系统完成自动路径调整的最大位置偏差和最大位姿偏角分别为0028mm和0026°,明显优于固定路径测试得到的0084mm和0095°,其位置偏差标准差与位姿偏角标准差分别提升了4倍和3倍。总之,本系统在自动化检测与控制领域具有一定的应用价值。     

耳温计检定系统机械臂位姿自动修正方法研究

针对耳温计自动检定系统中机械定位随机偏移的问题,提出一种基于机器视觉的机械臂位姿自动修正算法。在恒温槽基准位建立机械臂运动的基准参考坐标系,在此坐标系下设计机械臂作业路径动作;系统作业过程中,通过定位恒温槽上的特征图案生成变换矩阵,产生新参考坐标系;机械臂来到新参考坐标系下拍照,反推变换矩阵偏差值并对其迭代更新;通过对机械臂运动的参考坐标系进行修正,完成对机械臂三维作业的位姿修正。实验结果表明,所提算法对恒温槽上3个平面的定位精度达到0.5 mm以内,为相似场景下的视觉引导提供了一种新思路。     

六自由度工业机器人位姿误差的补偿方法

为了实现工业机器人的位姿误差补偿,在分析了机器人的位置误差和姿态误差的基础上,利用修正后的D-H算法建立了机器人运动学方程,并利用矩阵法建立了机器人的位姿误差分析模型。提出一种将机械结构参数综合映射到关节角度参数的补偿方法,并设计了一套适合此方法的补偿实验。通过对实验结果的分析与计算,验证了该方法适用于机器人位姿误差补偿,大幅度提高了机器人的绝对精度。     

非结构环境下机械臂各关节自动控制系统设计

为了使机械臂给工业企业带来更多利益,以智能化、低成本、小质量和高安全性能为目的,设计非结构环境下机械臂各关节自动控制系统。依据系统性能设计标准,为机械臂的肩膀、手肘和手腕处分别分配2DOF的自由度,给出机械臂D-H参数,并为各关节设计合适的电机来实现机械臂运动。在系统的FPGA中写入控制算法,使用主控芯片对不同关节处FPGA的控制算法进行融合,确定机械臂运动方案并下达控制指令,通过构造2.5D环境地图感知非结构环境,完善控制指令。从实验结果中可以看出所设计系统的关节轨迹优化能力强。     

基于激光测距的微型机械臂关节控制模型

为了更加深入探究并提升机械臂关节控制效果,提出一种基于激光测距的微型机械臂关节控制模型,通过激光测距技术对微型机械臂周边环境进行感知,同时进行数据点扫描,将全部数据点集进行直线分割以及拟合等相关操作,获取二维环境地图。在上述基础上,通过坐标变换矩阵获取微型机械臂的正运动学模型,利用正运动学模型得到机械臂逆运动学模型。将获取的动力学模型转换为仿射非线性系统的形式,利用输入输出反馈线性化方法选取合适的状态变换和反馈变换,通过滑膜控制方法构建微型机械臂关节控制模型,采用模型进行关节控制。仿真实验结果表明,所提模型可以获取理想的微型机械臂关节控制结果。     

基于三维激光扫描仪的无序工件精准定位北大核心CSCD

为了获取生产线上无序且被遮挡的工件的准确位姿,为后续机械臂对工件特定部位的抓取提供支持,本文使用高精度三维激光扫描仪扫描生产线上无序摆放的工件,然后对原始点云先后采用Voxel-Grid降采样、平面分割和DBSCAN聚类,分割出单个工件点云,再用K-4PCS粗配准和kd-tree加速的GICP精配准方法,将工件实际点云与标准的点云模板(由工件的机械设计图转化而来)进行配准,最终得到了两者之间精确的位姿变换矩阵,进而获得工件摆放的准确位姿。为了验证论文提出方法的有效性,对生产线上3组形状不同工件的摆放位姿进行了测试。结果表明,该方法对于不同形状的工件摆放位姿都有很好的求解精度(误差≤3 mm)。     

基于PSO算法优化的机械臂轨迹规划研究

目前机械臂轨迹规划的优化目标大多在最短路径、最优时间等方面且存在由于多项式差值轨迹规划具有阶次高、没有凸包性,难以应用传统优化方法进行优化等缺点。现提出了对最小能耗、最小加加速度等指标的优化。该优化是在传统时间最优的基础上,利用粒子群优化的4-3-4多项式插值轨迹规划算法,针对综合时间、能耗、加加速度等指标进行优化。实验以三关节机械臂为例进行仿真,结果证明了PSO优化过程和能耗函数的有效性。     

光交换中的半导体增益光开关门的研究

本文通过实验对双区共腔半导体增益光开关门的动态和静态光学特性（包括温度特性、偏振特性、光谱特性、偏置特性、开关特性及增益放大特性等）进行了分析研究，特别研究了其做为增益光开关门在光子交换系统中实现数据包交换功能的可行性，对半导体光开关门的数据包开关传输能力进行了原理性实验．文章最后提出了一种采用半导体增益光开关门构成的新颖的光子交换系统网络结构．     

基于机械臂路径规划的内场轨迹实现技术研究

为了解决传统光电跟踪设备的跟踪性能测试系统参数调试繁琐、设备安装困难、靶标适用性差等问题,研究了基于机械臂路径规划的内场轨迹实现技术。通过规划六自由度机械臂的末端运动轨迹,设计了更加灵活、高效的跟踪性能测试系统。首先,对传统测试靶标系统进行分析,明确实现跟踪性能测试的数学模型;然后提出基于六自由度机械臂的新型技术方案,并分析了两种方案的差异性;接着通过靶标轨迹的坐标变换,根据传统动态靶标轨迹得到适用于六自由度机械臂的末端位姿参数,从而实现轨迹规划;最后,通过数值仿真验证了本文方法与传统方法的跟踪性能测试效果的一致性。仿真结果表明,两者具有相同的跟踪性能测试效果。相较于传统方法,采用机械臂的测试系统在参数调节、工具安装和靶标适用性上更具优势,完全能够满足光电跟踪设备内场跟踪性能测试的要求。     

4-DOF多功能机器人运动控制算法的研究

随着机器人技术的不断发展,机器人在现在社会发展中发挥着越来越重要的作用。文中对实验室研发的多功能4-DOF机器人的运动控制相关问题进行研究。首先对4-DOF机器人的机构整体设计并PROE三维建模,然后通过基于D-H法建立机械臂坐标系,对4-DOF机器人进行运动学正逆解分析,在逆解计算中,提出了当两轴平行两轴耦合的计算方法,即将两轴关节角视为整体计算,再利用代数方法依次得出单个关节角。同时针对机械臂的连续轨迹运动给出轨迹规划的方法,为设计机械臂控制器的实现和机械臂的运动控制提供了依据。     

Development of a new 4-DOF endoscopic parallel manipulator based on screw theory for laparoscopic surgery

Development of rigid manipulators for Minimally Invasive Surgery (MIS) becomes essential to replace wire driven manipulators which are problematic due to possible cutting of the wire during the surgery. In this paper, a 4-DOF dexterous endoscopic parallel manipulator for MIS is designed and implemented. The manipulator is developed based on the concept of virtual chain and screw theory. The manipulator consists of four links; two links are 2-PUU (each leg consists of one active prismatic joint and two passive hook joints); the other two links are 2-PUS (each leg consists of one active prismatic join, one passive hook joint and one passive spherical joint). The inverse and forward kinematics solutions are derived analytically and numerically, respectively. The singularity analysis is investigated using screws algebra. The manipulator workspace is obtained using MATLAB software. The known problem of limited bending angles found in previous existing surgical manipulators was solved as the proposed manipulator can reach ±90° in any direction. The proposed surgical manipulator is designed, manufactured and tested successfully. The system model utilizing PID and PI controllers has been built using MATLAB software. Co-simulation using ADAMS/MATLAB software is implemented to validate the achieved bending angles and the proposed tracking control. The results show that the performance of the tracking control is satisfactory since the tracking error is about 2.5%.     

Singularity analysis of three-legged, six-DOF platform manipulators with URS legs

A special class of platform manipulators is the subject of this paper. These manipulators comprise two platforms connected by three legs, each being composed of one universal (U), one revolute (R) and one spherical (S) joints, which gives the manipulator six degrees of freedom. Hence, two actuators are required per leg. Under the assumption that the two R joints proximal to the fixed platform, and making up the U-joint, are actuated, we derive the differential kinematic relations between actuator joint rates and mobile-platform twist. This model comprises two Jacobian matrices, the forward- and inverse-kinematics Jacobians. These relations are then applied to the singularity analysis of the parallel manipulator developed at Singapore Institute of Manufacturing Technology and Nanyang Technological University.     

Force feedback control of robot manipulator by the accelerationtracing orientation method

The authors propose a novel approach to force and compliance control of multi-degree-of-freedom (DOF) robot manipulators. The acceleration tracing orientation method (ATOM) is applied to both controllers. The control law is described in the Cartesian space; however, the final command is the acceleration in the joint space. The interactive terms in each joint disturb and deteriorate the joint motion. The disturbance observer cancels out the total sum of these terms and enables each joint to trace the acceleration command. As a result, a robust control is possible in the force task. The testing of the proposed system in a three-DOF robot manipulator is discussed     

Neural network-based control of balanced robotic manipulators with joint flexibility

This paper addresses an improvement on the controlled performance of balanced manipulators in a practical level by implementing neural network based controller. The mass balancing of robotic manipulators has been shown to have favorable effects on the dynamic characteristics. However, it was also pointed out that for the manipulators having a certain degree of flexibility at the joints, due to the lowered structural natural frequencies and reduced velocity related terms, mass balancing results in vibratory motion at high speed operation. Such a vibratory tendency of the balanced flexible joint manipulator limits the admissible range of servo gains of the conventional controllers, making those controllers unsuitable for controlling the manipulator at high speeds.

To avoid such difficulty, an artificial neural network (NN) controller is introduced to realize the dynamic control of the balanced flexible joint manipulators. A feedforward type of NN controller is proposed and its performance is evaluated through a series of numerical simulations. The proposed NN controller showed much better tracking performances over the conventional PD controller.     

Control of redundant manipulators considering order of disturbanceobserver

A manipulator control method using a disturbance observer with no inverse dynamics has been proposed. The order of the disturbance observer affects the performance of control system, because nominalization of plant is dependent on the control object and the order of the disturbance observer. This paper proposes a unique choice of disturbance observers of different order in joint and task space to improve system performance of hybrid position/force control of redundant manipulators. Also, it has been shown that a proper selection of a coefficient of the disturbance observer is capable to improve robust stability, while not influencing basic performance. The proposed strategy can realize acceleration control and second derivative of force control in the task space, which realizes robust and precise control of manipulators. Experimental results using a redundant manipulator show the effectiveness of the proposed strategy     

Neural Network-Based Kinematic Inversion of Industrial Redundant Robots Using Cooperative Fuzzy Hint for the Joint Limits Avoidance

In this paper, a neural network (NN)-based inverse kinematics problem of redundant manipulators subject to joint limits is presented. The Widrow–Hoff NN with an adaptive learning algorithm derived by applying Lyapunov stability theory is introduced. Since the inverse kinematics has an infinite number of joint angle vectors, a fuzzy neural network (FNN) is designed to provide an approximate value for that vector. This vector is fed into the NN as a hint input vector to guide the output of the NN within the self motion. This FNN is designed on the basis of cooperatively controlling each joint angle in the sense that it stops the motion on the critical axis at its limit at the expense of greater compensation from the most relaxed joint to accomplish the task. Physical constraints such as the joint velocity limits as well as the joint angle limits are incorporated into the method. Experiments are conducted for the PA-10 redundant manipulator to show the effectiveness of the proposed control system. A comparative study is carried out with the gradient projection method.     

A fractional approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots through the pseudoinverse control leads to undesirable drift in the joint space. This paper presents a new technique to solve the inverse kinematics problem of redundant manipulators, which uses a fractional differential of order α to control the joint positions. Two performance measures are defined to examine the strength and weakness of the proposed method. The positional error index measures the precision of the manipulator's end-effector at the target position. The repeatability performance index is adopted to evaluate if the joint positions are repetitive when the manipulator execute repetitive trajectories in the operational workspace. Redundant and hyper-redundant planar manipulators reveal that it is possible to choose in a large range of possible values of α in order to get repetitive trajectories in the joint space.     

An optimization-based approach for elasticity-aware trajectory planning of link-elastic manipulators

Elastic manipulators often result from lightweight construction or safety requirements in human–robot-collaboration scenarios. In many cases, vibration-damping becomes necessary to enable stable and precise operation, which imposes high demands on controllers. A fundamental challenge for link-elastic manipulators with general kinematics and no dedicated damping actuators is the potential inability of a joint to control the vibration of a link depending on the manipulator’s configuration. Numerous control concepts assume a sufficiently high ability to control vibrations by, for example, dedicated actuators or special kinematic structures. This work presents an online, optimization-based motion planning approach with three methods for maximizing this ability for link-elastic manipulators. The planning algorithm utilizes modified cost functions to incorporate the controllability of vibrations by prioritization and adaptive activation of competing objectives. The effectiveness of the approach is demonstrated on a real manipulator with 3 actuated DoFs and two elastic links in different disturbance scenarios. The results show that the amplitudes of vibrations caused by disturbances decay noticeably faster than with conventional motion planning.     

Kinematic calibration of Orthoglide-type mechanisms from observation of parallel leg motions

The paper proposes a new calibration method for parallel manipulators that allows efficient identification of the joint offsets using observations of the manipulator leg parallelism with respect to the base surface. The method employs a simple and low-cost measuring system, which evaluates deviation of the leg location during motions that are assumed to preserve the leg parallelism for the nominal values of the manipulator parameters. Using the measured deviations, the developed algorithm estimates the joint offsets that are treated as the most essential parameters to be identified. The validity of the proposed calibration method and efficiency of the developed numerical algorithms are confirmed by experimental results. The sensitivity of the measurement methods and the calibration accuracy are also studied.     

A nonlinear disturbance observer for robotic manipulators

A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well