机器人砂带磨削系统作业精度分析与误差补偿

为了更好地反映及提高工业机器人砂带磨削系统的整体性能,通过分析机器人应用系统的特点,详细 描述了工业机器人应用系统“作业精度”的含义及衡量标准．在此基础上,推导了机器人砂带磨削系统作业精度模 型,设计了机器人砂带磨削系统作业误差测量工具及校准系统,建立了实际的机器人砂带磨削系统．通过实际的机 器人磨削实验验证了方法的有效性．     

A novel kinematic parameters calibration method for industrial robot based on Levenberg-Marquardt and Differential Evolution hybrid algorithm

The poor absolute positioning accuracy of industrial robots is the main obstacle for its further application in precision grinding of complex surfaces, such as blisk, blade, etc. Based on the established kinematic error model of a typical industrial robot FANUC M710ic/50, a novel kinematic parameters calibration method is proposed in this paper to improve the absolute positioning accuracy of robot. The pre-identification of the kinematic parameter deviations of robot was achieved by using the Levenberg-Marquardt algorithm. Subsequently, these identified suboptimal values of parameter deviations were defined as central values of the components of initial individuals to complete accurate identification by using Differential Evolution algorithm. The above two steps, which were regarded as the core of this Levenberg-Marquardt and Differential Evolution hybrid algorithm, were used to obtain the preferable values for kinematic parameters of the robot. On this basis, the experimental investigations of kinematic parameters calibration were conducted by using a laser tracker and numerical simulation method. The results revealed that the robot positioning error decreased from 0.994 mm, initial positioning error measured by laser tracker, to 0.262 mm after calibration with this proposed hybrid algorithm. The absolute positioning accuracy has increased by 40.86% than that of the Levenberg-Marquardt algorithm, increased by 40.31% than that of the Differential Evolution algorithm, and increased by 25.14% than that of the Simulated Annealing algorithm. This work shows that the proposed kinematic parameters calibration method has a significant improvement on the absolute positioning accuracy of industrial robot.     

An adaptive trajectory planning algorithm for robotic belt grinding of blade leading and trailing edges based on material removal profile model

Robotic belt grinding of the leading and trailing edges of complex blades is considered to be a challenging task, since the microscopic material removal mechanism is complicated due to the flexible contact state accompanied with greatly varying curvature that finally affects the machined profile accuracy. The resulting poor accuracy of blade edges, to a great extent, is attributed to the trajectory planning method which less considers the dynamics. In this paper, an iso-scallop height algorithm based on the material removal profile (MRP) model is developed to plan the tool paths by taking into consideration the elastic deformation at contact wheel-workpiece interface. An improved constant chord-height error method considering the influence of elastic deformation is then proposed to adaptively plan the grinding points according to the curvature change characteristics of the free-form surface. Based on these two steps, a MRP model based adaptive trajectory planning algorithm is constructed to enhance the profile accuracy facing the robotic belt grinding operation. Simulation and experimental results demonstrate the effectiveness of the proposed trajectory planning algorithm for the robotic belt grinding of blades from the perspectives of surface roughness, profile accuracy and processing efficiency. Particularly this technology serves to solve the problem of over-cutting at the blade leading and trailing edges.     

Predictive seam tracking with iteratively learned feedforward compensation for high-precision robotic laser welding

In this paper, a novel architecture for robotic seam tracking using an industrial robot and off-the-shelf sensors is proposed to compensate the residual errors that are commonly observed in high-precision robotic laser welding due to the nonlinearity of a seam and the fast path drifts along a robot path. Our experiments demonstrate that the robot system can track both linear and nonlinear long seams at a high speed of 100 mm/s with TCP offset-error within ±0.1 mm using the proposed method.     

基于量子遗传算法的移动机器人的一种路径规划方法

以人工势场法和栅格法为基础,考虑到遗传算法的“收敛速度慢”和“早熟收敛”问题,提出了一种基于量子遗传算法的机器人路径规划方法。该方法采用栅格法进行路径规划,利用人工势场法控制移动机器人,利用量子遗传算法选择最优或次优个体,并且引入双适应度评价函数评价进化个体,为最优或次优个体进入下一代提供了保障。仿真实验表明,该方法的寻优能力及稳定性均优于遗传算法和量子遗传算法,且具有更好的收敛性以及更强的连续空间搜索能力,适于求解复杂优化问题。     

Automatic joint motion planning of 9-DOF robot based on redundancy optimization for wheel hub polishing

Automatic joint motion planning is very important in robotic wheel hub polishing systems. Higher flexibility is achieved based on the joint configuration with multiple solutions, which means that the robot has kinematic redundancy for machining tasks. Redundant joints can be used to optimize the motion of the robot, but less research has been done on multi-dimensional redundant optimization. In this paper, a 6-axis robot with a 3-axis actuator is designed for wheel hub polishing. We propose an automatic joint motion planning method for a nine-axis industrial robot to achieve the shortest processing time. Firstly, offline programming is designed to generate paths for the complex surface of the hub. In order to reduce the machining path points on the surface of the hub, a improved Douglas-Peucker (DP) algorithm is proposed, which can take into account the change of the path point posture. Secondly, the Greedy Best First Search (GBFS) and Sine cosine algorithm (SCA) are combined to find the optimal joint motion efficiently. Moreover, we use nested SCA for comparison to test whether the combined algorithm can avoid local optima. Finally, the performance and computational efficiency of the method are validated in both simulation and real environments based on the hub surface.     

Dynamic performance of industrial robot in corner path with CNC controller

The industrial robot has already been used for machining tasks in the industry. In order to improve the machining accuracy, a CNC controller is proposed as a control system for the industrial robot. This article concentrates on the performance of the industrial robot motion accuracy guided by a CNC controller. Corner paths are studied in consideration of different running speeds. The path accuracy and the influence of motion acceleration are both thoroughly analyzed. The performance of the same paths running in a conventional controller is evaluated for comparison.     

A neural network approach to complete coverage path planning.

Complete coverage path planning requires the robot path to cover every part of the workspace, which is an essential issue in cleaning robots and many other robotic applications such as vacuum robots, painter robots, land mine detectors, lawn mowers, automated harvesters, and window cleaners. In this paper, a novel neural network approach is proposed for complete coverage path planning with obstacle avoidance of cleaning robots in nonstationary environments. The dynamics of each neuron in the topologically organized neural network is characterized by a shunting equation derived from Hodgkin and Huxley's (1952) membrane equation. There are only local lateral connections among neurons. The robot path is autonomously generated from the dynamic activity landscape of the neural network and the previous robot location. The proposed model algorithm is computationally simple. Simulation results show that the proposed model is capable of planning collision-free complete coverage robot paths.     

Time-varying isobaric surface reconstruction and path planning for robotic grinding of weak-stiffness workpieces

Severe deformations and vibration usually occur when grinding the weak-stiffness workpieces, then fluctuate the grinding force and damage the surface. In this paper, the time-varying isobaric surface (TVIS) is defined as a virtual surface to generate constant force during robotic grinding. Based on it, a novel robotic grinding method, including contact trial and surface reconstruction, is proposed. In the contact trial process, the robot actively samples the deformation and stiffness of contact point with a force sensor. Then, a TVIS mesh is constructed to replace the original geometry of the workpiece, which is utilized for grinding path planning. Experiments have been conducted to verify the feasibility of this method. The result shows that the proposed method can achieve constant grinding force and is robust to the types of workpieces and the processing techniques. Furthermore, it is considered as an intelligent method for customized robotic machining of the weak-stiffness workpieces.     

基于准确度评估的7自由度手术机器人术前摆位优化算法

针对微创机器人辅助的外科手术复杂的术前摆位问题,以甲状腺微创手术用到的床旁双7自由度协作机器人为研究对象,将机械臂的运动准确度以及运动学性能作为优化目标,提出了机械臂准确度评估指标以及其对应的干涉指数,并提出了一套基于带精英策略的非支配排序遗传算法（NSGA-Ⅱ）多目标遗传算法的术前规划方法。最后,将由该遗传算法优化得...     

Image‐guided robotic navigation system for neurosurgery

This paper presents an image‐guided robotic navigation system for neurosurgery, which can be applied to the electro‐stimulation treatment of Parkinson's leisure, the biopsy of deep tumors, and haematoma evacuation. The system integrates a computer containing CT images for surgical planning, a magnetic tracking device for measuring the coordinates of the markers and surgical instruments, and a robot manipulator for guiding surgical instruments to the preplanned position and orientation. The computer display of brain anatomy offers a convenient tool for surgeons to diagnose brain diseases and to plan safe surgical paths, while the tracking device guides the robot manipulator to automatically move surgical instruments to the preplanned position and orientation. An experiment of using a skull model for simulating a robotic biopsy of brain tumor has been done to verify the performance of the robotic navigation system. The results show that the positioning accuracy of the robot relative to the tracker frame is only related to the positioning resolution of the robot manipulator and the positioning accuracy of the tracking device. In other words, the positioning accuracy of the robot manipulator does not affect the final positioning accuracy of the surgical instruments. Therefore, using a robot manipulator for precise surgical navigation is feasible and reliable. © 2000 John Wiley & Sons, Inc.     

基于三坐标测量机的机器人位姿精度检测方法

针对医疗场合导航引导下的手术机器人定位精度检测问题,提出了基于三坐标测量机的机器人位姿距离精度测量方法。该方法通过放置在一个平面上的三个标准球来实现三坐标测量机对姿态精度的测量,并参照机器人辅助外科手术系统的定位原理构建基于三坐标测量机的机器人位姿检测平台。在此基础上,依据国家标准规定的机器人性能检测方法和过程,完成机器人位姿距离精度的测量。通过该方法对研发的骨科手术定位机器人进行测量的结果表明,所设计机器人位置距离准确度和重复性分别在[10-1]mm和[10-2]mm级别,姿态距离准确度和重复性分别在[10-1]度和[10-2]度级别。最后将该机器人应用于前交叉韧带重建手术实验,结果表明通过这种方法检测的机器人能够满足手术场合要求。     

Adaptive Partial Shortcuts: Path Optimization for Industrial Robotics

The quality of a path generated from an automated motion planning algorithm is of considerable importance, particularly when used in a real world robotic application. In this work a new path optimization algorithm, called the Adaptive Partial Shortcut algorithm, is presented. This algorithm optimizes paths as a post process to motion planning, and is designed specifically for use on industrial manipulators. The algorithm optimizes a robot’s degrees of freedom independently allowing it to produce manipulator paths of particularly high quality. This new algorithm utilizes an adaptive method of selecting the degree of freedom to optimize at each iteration, giving it a high level of efficiency. Tests conducted show the effectiveness of the algorithm; over a range of different test paths, the adaptive algorithm was able to generate solutions with a 60 % reduction in collision checks compared to the original partial shortcut approach.     

Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces

A time-optimal motion planning method for robotic machining of sculptured surfaces is reported in this paper. Compared with the general time-optimal robot motion planning, a surface machining process provides extra constraints such as tool-tip kinematic limits and complexity of the curved tool path that also need to be taken into account. In the proposed method, joint space and tool-tip kinematic constraints are considered. As there are high requirements for tool path following accuracy, an efficient numerical integration method based on the Pontryagin maximum principle is adopted as the solver for the time-optimal tool motion planning problem in robotic machining. Nonetheless, coupled and multi-dimensional constraints make it difficult to solve the problem by numerical integration directly. Therefore, a new method is provided to simplify the constraints in this work. The algorithm is implemented on the ROS (robot operating system) platform. The geometry tool path is generated by the CAM software firstly. And then the whole machine moving process, i.e. the feedrate of machining process, is scheduled by the proposed method. As a case study, a sculptured surface is machined by the developed method with a 6-DOF robot driven by the ROS controller. The experimental results validate the developed algorithm and reveal its advantages over other conventional motion planning algorithms for robotic machining.     

A non-contact laser speckle sensor for the measurement of robotic tool speed

A non-contact speckle correlation sensor for the measurement of robotic tool speed is described that is capable of measuring the in-plane relative velocities between a robot end-effector and the workplace or other surface. The sensor performance has been assessed in the laboratory with sensor accuracies of ±0.01 mm/s over a ±70 mm/s velocity range. The effect of misalignment of the sensor on the robot was assessed for variation in both working distance and angular alignment with sensor accuracy maintained to within 0.025 mm/s (<0.04%) over a working distance variation of ±5 mm from the sensor design distance and ±0.4 mm/s (0.6%) for a misalignment of 5°. The sensor precision was found to be limited by the peak fitting accuracy used in the signal processing with peak errors of ±0.34 mm/s. Finally an example of the sensor’s application to robotic manufacturing is presented where the sensor was applied to tool speed measurement for path planning in the wire and arc additive manufacturing process using a KUKA KR150 L110/2 industrial robot.     

Path planning for grasping operations using an adaptive PCA-based sampling method

The planning of collision-free paths for a hand-arm robotic system is a difficult issue due to the large number of degrees of freedom involved and the cluttered environment usually encountered near grasping configurations. To cope with this problem, this paper presents a novel importance sampling method based on the use of principal component analysis (PCA) to enlarge the probability of finding collision-free samples in these difficult regions of the configuration space with low clearance. By using collision-free samples near the goal, PCA is periodically applied in order to obtain a sampling volume near the goal that better covers the free space, improving the efficiency of sampling-based path planning methods. The approach has been tested with success on a hand-arm robotic system composed of a four-finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) and an industrial robot (6 independent degrees of freedom).     

A Non-Time Based Controller for Load Swing Damping and Path-Tracking in Robotic Cranes

This paper proposes the use of the non-time based control strategy named Delayed Reference Control (DRC) to the control of industrial robotic cranes. Such a control scheme has been developed to achieve two relevant objectives in the control of autonomous operated cranes: the active damping of undesired load swing, and the accurate tracking of the planned path through space, with the preservation of the coordinated Cartesian motion of the crane. A paramount advantage of the proposed scheme over traditional ones is its ease of implementation on industrial devices: it can be implemented by just adding an outer control loop (incorporating path planning) to standard position controllers. Experimental performance assessment of the proposed control strategy is provided by applying the DRC to the control of the oscillation of a cable-suspended load moved by a parallel robot mimicking a robotic crane. In order to implement the DRC scheme on such an industrial robot it has been just necessary to manage path planning and the DRC algorithm on a separate real-time hardware computing the delay in the execution of the desired trajectory suitable to reduce load swing. Load swing has been detected by processing the images from two off-the-shelf cameras with a dedicated vision system. No customization of the robot industrial controller has been necessary.     

Path Planning for a Statically Stable Biped Robot Using PRM and Reinforcement Learning

In this paper path planning and obstacle avoidance for a statically stable biped robot using PRM and reinforcement learning is discussed. The main objective of the paper is to compare these two methods of path planning for applications involving a biped robot. The statically stable biped robot under consideration is a 4-degree of freedom walking robot that can follow any given trajectory on flat ground and has a fixed step length of 200 mm. It is proved that the path generated by the first method produces the shortest smooth path but it also increases the computational burden on the controller, as the robot has to turn at almost all steps. However the second method produces paths that are composed of straight-line segments and hence requires less computation for trajectory following. Experiments were also conducted to prove the effectiveness of the reinforcement learning based path planning method.     

Optimization-based path planning framework for industrial manufacturing processes with complex continuous paths

The complexity of robotic path planning problems in industrial manufacturing increases significantly with the current trends of product individualization and flexible production systems. In many industrial processes, a robotic tool has to follow a desired manufacturing path most accurately, while certain deviations, also called process tolerances and process windows, are allowed. In this work, a path planning framework is proposed, which systematically incorporates all process degrees of freedom (DoF), tolerances and redundant DoF of the considered manufacturing process as well as collision avoidance. Based on the specified process DoF and tolerances, the objective function and the hard and soft constraints of the underlying optimization problem can be easily parametrized to find the optimal joint-space path. By providing the analytical gradients of the objective function and the constraints and utilizing modern multi-core CPUs, the computation performance can be significantly improved. The proposed path planning framework is demonstrated for an experimental drawing process and a simulated spraying process. The planner is able to solve complex planning tasks of continuous manufacturing paths by systematically exploiting the process DoF and tolerances while allowing to move through singular configurations, which leads to solutions that cannot be found by state-of-the-art concepts.     

砂带磨削机器人的灵活性分析与优化

总结了磨削机器人的当前发展和阻碍砂带磨削机器人广泛应用的难点．根据复杂曲面磨削任务对机器 人的实际要求,提出了一种磨削机器人构型．这种机器人属于PPPRRR 构型,具有很高的定位精度和结构刚度．利 用旋量理论中的指数积公式推导了该机器人的运动学正反解．引入了模拟退火算法,分析获得了相对于末端坐标系 描述的砂带磨削机器人的灵活磨削空间,并绘制了灵活磨削空间的横截面图谱．进一步,采用模式搜索法,优化了 磨削机接触轮相对于机器人基坐标系的位移偏移量,获得了最大的灵活磨削空间体积,提高了机器人砂带磨削系统 的灵活性．