Posture optimization methodology of 6R industrial robots for machining using performance evaluation indexes

For industrial robots, the relatively low posture-dependent stiffness deteriorates the absolute accuracy in the robotic machining process. Thus, it is reasonable to consider performing machining in the regions of the robot workspace where the kinematic, static and even dynamic performances are highest, thereby reducing machining errors and exhausting the advantages of the robot. Simultaneously, an optimum initial placement of the workpiece with respect to the robot can be obtained by optimizing the above performances of the robot. In this paper, a robot posture optimization methodology based on robotic performance indexes is presented. First, a deformation evaluation index is proposed to directly illustrate the deformation of the six-revolute (6R) industrial robot (IR) end-effector (EE) when a force is applied on it. Then, the kinematic performance map drawn according to the kinematic performance index is utilized to refine the regions of the robot workspace. Furthermore, main body stiffness index is proposed here to simplify the performance index of the robot stiffness, and its map is used to determine the position of the EE. Finally, the deformation map obtained according to the proposed deformation evaluation index is used to determine the orientation of the EE. Following these steps, the posture of the 6R robot with the best performance can be obtained, and the initial workpiece placement can be consequently determined. Experiments on a Comau Smart5 NJ 220-2.7 robot are conducted. The results demonstrate the feasibility and effectiveness of the present posture optimization methodology.     

Region-based toolpath generation for robotic milling of freeform surfaces with stiffness optimization

Because of industrial robots’ relatively low stiffness, many research efforts have been performed to improve the robot stiffness by optimizing the robot posture. For freeform surfaces with large curvature, however, the expected high stiffness posture may undergo excessive changes that exceed the robot joint speed limit. Therefore, the stiffness optimization may not achieve the expected results in actual machining owing to the limitation of robot kinematics and conventional toolpath pattern. To address this problem, a region-based toolpath generation method is proposed to improve robot stiffness in this study for robotic milling of freeform surfaces. To provide the possibility of higher stiffness robot posture, not only the redundant degree of freedom (DOF) of the robot but also the orientation of tool axis during machining is optimized. Under the influence of surface curvature and position, the change of high stiffness posture has regionality. A surface subdivision method is proposed to divide the surface into multiple sub-regions, so that actual robot posture with better stiffness can be obtained. For each sub-region, the feed direction of toolpath is optimized to further enhance robot stiffness. Simulations and experimental studies are conducted, and show that the proposed toolpath generation method can improve the robot stiffness in freeform surface machining.     

Elasto-geometrical error and gravity model calibration of an industrial robot using the same optimized configuration set

Position error is a significant limitation for industrial robots in high-precision machining and manufacturing. Efficient error measurement and compensation for robots equipped with end-effectors are difficult in industrial environments. This paper proposes a robot calibration method based on an elasto–geometrical error and gravity model. Firstly, a geometric error model was established based on the D-H method, and the gravity and compliance error models were constructed to predict the elastic deformation caused by the self-weight of the robot. Subsequently, the position error model was established by considering the attitude error of the robot flange coordinate system. A two-step robot configuration selection method was developed based on the sequential floating forward selection algorithm to optimize the robot configuration for calibrating the position error and gravity models. Then, the geometric error and compliance coefficient were identified simultaneously based on the hybrid evolution algorithm. The gravity model parameters were identified based on the same algorithm using the joint torque signal provided by the robot controller. Finally, calibration and compensation experiments were conducted on a KR-160 industrial robot equipped with a spindle using a laser tracker and internal robot data. The experimental results show that the robot tool center point error can be significantly improved by using the proposed method.     

Profile error-oriented optimization of the feed direction and posture of the end-effector in robotic free-form milling

In robotic milling of free-form surfaces, most existing studies tried to reduce the profile errors by optimizing the robot stiffness. However, the stiffness could not directly and rigorously reflect the milling performance to some content, especially, when the significant influence of feed direction on the profile error was ignored for robotic milling of free-form surfaces with large curvatures. In order to solve these problems, direct optimization of the feed directions and end-effector postures is theoretically formulated to seek the solution of a new profile error-oriented optimization model. This model characterizes the profile error in relation to the robot deformation caused by cutting forces, called force-induced profile error. The force-induced profile error is calculated and reduced at each cutter contact point on the free-form surface by comprehensively considering robot stiffness, free-form surface features, feed directions and cutting forces for generating feed direction and posture of the end-effector. The surface is partitioned into multiple sub-regions, in each of which the principle for determining the initial feed direction is proposed to ensure the smooth milling without abrupt change of feed direction. Robotic milling process of the workpiece with saddle contour is experimented. Feed direction and posture of the end-effector are generated by the proposed method and the existing method for comparative studies. Measured profile errors and photographs of machined surface indicate that the developed method can greatly improve the milling performance.     

Dynamic grasp planning of multifingered robot hands based onasymptotic stability

We describe an approach for planning grasps of multifingered robot hands based on a small vibration model. Using features of the grasp configuration, we analyze asymptotic stability, contact situations, and uniaxial fingertip force constraints for the combined planning of finger posture and finger position, and characterize the generalized mass, damping, and stiffness. Choosing the largest time constant of the vibration model as an optimization criterion for planning finger postures and positions, the original problem of dynamic grasp planning is formulated as a nonlinear program. Simulation examples for a three-fingered robot hand grasping a spherical object demonstrate the effectiveness of the approach.     

Robotic milling posture adjustment under composite constraints: A weight-sequence identification and optimization strategy

Industrial robots are widely used for milling complex parts in restricted spaces owing to their multiple degrees of freedom and flexible postures. To plan posture trajectory for robot machining with high precision under multiple constraints, this study establishes composite constraint models with constraint boundary solutions. An improved gray relation analysis model is adopted to identify the weight-sequences among the composite constraints. The correlation degrees of the postures of the robot can be dynamically quantified between arbitrary cutter locations by applying weight sequence identification, which is conducive to fulfilling attractive orientations in artificial potential fields. In addition, this study proposes an initial posture determination strategy based on the optimization principle of minimizing the rotated energy in global postures. Consequently, an artificial potential planning model is applied to the implement posture adjustment of the robot end effector. During simulation and experimental validation, the proposed posture adjustment strategies with optimized initial postures and identified weight-sequences achieve a significant improvement in both the six-joint motion performance and machining precision quality in robotic milling.     

基于刚柔耦合模型的仿生鸭机器人运动分析

通过Hypermesh有限元软件及Adams动力学软件建立了所设计的一种仿生鸭机器人的刚柔耦合模型以更好地模拟真实的运行工况.计算了小腿的动态受力及形变情况,并分析了影响蹼足运动参数的两种因素,即小腿结构是否形变及腿部关节摩擦系数.结果表明：在机器人运行过程中,小腿满足强度和刚度要求；小腿形变导致的蹼足运动学参数误差会使机器人运行时的精确性变差；对关节进行润滑可以减小机器人移动时受到的冲击.仿真计算结果可为后续机器人结构优化提供数据参考.     

Position-oriented process monitoring in milling of thin-walled parts

Improving machining performance of thin-walled parts is of great significance in aviation industry, since most aviation parts are characterized by large size, complex shape, and thin-walled structure. Machining process monitoring is the essential premise to improve the machining performance. In order to improve the machining quality and efficiency, this paper presents a position-oriented process monitoring model based on multiple data during milling process, and corresponding solution is provided. Through obtaining the internal data set of the numerical control (NC) system during machining, it is possible to correlate the cutting position with monitoring signals including cutting force, acceleration, and spindle power. Then, process optimization is realized to improve the machining quality and efficiency based on the monitoring results. Machining tests are conducted on aircraft structural part as well as blade part, and the experimental results show this method provides a significant insight into the machining process of thin-walled part and contributes to the process optimization. By using feedrate optimization, time consumption for the rough milling process of one titanium alloy part reduced from 19.1 h to 14.4 h and the number of cutter consumption dropped from 5 to 3. And according to the result of position-oriented process monitoring, the machining strategies were optimized to reduce vibration and avoid chatter, thereby improving the machining quality.     

Joint stiffness identification of six-revolute industrial serial robots

Although robots tend to be as competitive as CNC machines for some operations, they are not yet widely used for machining operations. This may be due to the lack of certain technical information that is required for satisfactory machining operation. For instance, it is very difficult to get information about the stiffness of industrial robots from robot manufacturers. As a consequence, this paper introduces a robust and fast procedure that can be used to identify the joint stiffness values of any six-revolute serial robot. This procedure aims to evaluate joint stiffness values considering both translational and rotational displacements of the robot end-effector for a given applied wrench (force and torque). In this paper, the links of the robot are assumed to be much stiffer than its actuated joints. The robustness of the identification method and the sensitivity of the results to measurement errors and the number of experimental tests are also analyzed. Finally, the actual Cartesian stiffness matrix of the robot is obtained from the joint stiffness values and can be used for motion planning and to optimize machining operations.     

Dynamic and static characteristics of a hydrostatic spindle for machine tools

The objective of this work is to study the static and dynamic behavior of a shaft supported by hydrostatic bearings. The hydrostatic bearing consists of a thrust bearing and a radial bearing fed by orifice restrictors. The radial bearing consists of six rectangular symmetry oil pockets that have the same depth; the thrust bearing consists of eight fan-shaped oil pockets. Static and dynamic modeling was performed in order to investigate the effect of the eccentricity ratio on the film thickness, stiffness and deformation of a spindle system. In the first step, the deformation of the spindle caused by the parameter change is studied according to a static model. In the second step, the vibration response caused by the eccentricity is analyzed with a dynamic model. In the third step, the effect of imbalanced vibration on the machining accuracy is analyzed; the imbalance-induced force in two directions is derived from the dynamic results. This research shows that the location and stiffness of the bearing affect the machining accuracy to a high degree.     

Posture/Walking Control for Humanoid Robot Based on Kinematic Resolution of CoM Jacobian With Embedded Motion

This paper proposes the walking pattern generation method, the kinematic resolution method of center of mass (CoM) Jacobian with embedded motions, and the design method of posture/walking controller for humanoid robots. First, the walking pattern is generated using the simplified model for bipedal robot. Second, the kinematic resolution of CoM Jacobian with embedded motions makes a humanoid robot balanced automatically during movement of all other limbs. Actually, it offers an ability of whole body coordination to humanoid robot. Third, the posture/walking controller is completed by adding the CoM controller minus the zero moment point controller to the suggested kinematic resolution method. We prove that the proposed posture/walking controller brings the disturbance input-to-state stability for the simplified bipedal walking robot model. Finally, the effectiveness of the suggested posture/walking control method is shown through experiments with regard to the arm dancing and walking of humanoid robot.     

Robot-process precision modelling for the improvement of productivity in flexible manufacturing cells

Industrial robots are traditionally used at machining cells for machine feeding and workpiece handling. A reassignment of tasks to improve the productivity requires a modelling of the robot behaviour from the point of view of its position precision. This paper characterizes and predicts the precision achievable when drilling with an industrial robot in order to use it in machining operations.Robot behaviour and drilling phenomena are analysed to determine working accuracy and their contribution in position deviation and uncertainty. An efficient model for drilling is developed, applying quaternions and considering the influence of all cutting tool angles, providing a very precise estimation of drilling torques and forces. An innovative model for the robot is developed based on multibody systems, using mixed natural coordinates that enhance the computing and deliver outputs with direct interpretation. Besides, the effect of stiffness is added in joints as additional element.The complete robot-process model shows the significative process influence in working precision against robot influence. This influence is responsible of up to 40% of the total uncertainty. The model and the tests performed show that the deviations and their uncertainties depend strongly on drilling forces and the robot configuration. In the other hand, the model allows to correct the systematic behaviour in robot deviations and improve with that the position tolerance of the holes to be drilled.     

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.     

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.     

Base position optimization of mobile manipulators for machining large complex components

With good mobility and high flexibility, the mobile manipulator shows a broad application prospect in the machining of large complex components. In these applications, in order to fully utilize the capabilities of the robot, it is usually necessary to design a series of suitable working positions (i.e. robot's base position) for the mobile manipulator. However, the performance distribution of the robot in the task space is highly nonlinear, which makes it difficult to determine the optimal base positions. Therefore, this paper proposes a new base position optimization method, which can accurately find the optimal base position that takes into account both kinematics and stiffness performance. First, a task-oriented performance index MSPI (mean stiffness performance index) is proposed to evaluate the global stiffness performance of the robot. Based on MSPI, an optimization model considering multiple constraints such as joint range, joint speed, singular avoidance and collision avoidance is established. The optimization model is solved by sparse uniform grid decomposition and Sequential Quadratic Programming (SQP) method, the former is used to find a suitable initial value, the latter is used to determine the optimal base position. Finally, simulation analysis and experiments confirmed the effectiveness of the optimization method and the correctness of the performance index MSPI.     

A comparative study on some navigation schemes of a real robot tackling moving obstacles

A comparative study of various robot motion planning schemes has been made in the present study. Two soft computing (SC)-based approaches, namely genetic-fuzzy and genetic-neural systems and a conventional potential field method (PFM) have been developed for this purpose. Training to the SC-based approaches is given off-line and the performance of the optimal motion planner has been tested on a real robot. Results of the SC-based motion planners have been compared between themselves and with those of the conventional PFM. Both the SC-based approaches are found to perform better than the PFM in terms of traveling time taken by the robot. Moreover, the performance of fuzzy logic-based motion planner is seen to be comparable with that of neural network-based motion planner. Comparisons among all these three motion planning schemes have been made in terms of robustness, adaptability, goal reaching capability and repeatability. Both the SC-based approaches are found to be more adaptive and robust compared to the PFM. It may be due to the fact that there is no in-built learning module in the PFM and consequently, it is unable to plan the velocity of the robot properly.     

Feedforward operational stiffness modulation and external force estimation of planar robots equipped with variable stiffness actuators

A variable stiffness actuator (VSA) is considered a promising mechanism-based approach for realizing compliant robotic manipulators. By changing the stiffness of each joint, the robot can modulate the stiffness of the entire system to enhance safety and efficiency during physical interaction with other systems. This paper presents a feedforward method to modulate the operational stiffness of a parallel planar robot with multiple VSAs. A VSA utilizing a lever mechanism was developed, clearly presenting its mechanical design and kinematic model details. A computational model of joint-restoring torque was developed based on deformation measurements and hysteresis loop geometry to estimate the applied torque of each joint in real-time. An algorithm was proposed to compute the joint stiffness solution using the robot's kinematic model for modulating the operational stiffness of the parallel robot. Experiments were performed to evaluate the proposed method by comparing the performances of two DOF serial and parallel robot systems. The results demonstrated the capability of the VSA in both feedforward stiffness modulation and external force estimation.

     

高精度重载搅拌摩擦焊机器人设计与运动控制

针对高强度大型复杂曲面零件的高精度搅拌摩擦焊需求,研制开发了一种重载搅拌摩擦焊（friction stir welding,FSW）机器人．为使机器人具有大工作空间与灵巧作业能力,选择串联机构作为机器人构型,并阐述了高精度重载机构的设计与刚度校核方法．推导了腕关节含间隙的动力学模型,提出了双电机消隙控制方法,并对不同负载与偏置电流下的消隙效果进行了仿真分析,结果显示主动消隙方法能有效抑制传动间隙造成的位置波动与误差．为消除z轴在自重与焊接力作用下的挠度变形,提出了一种挠度主动补偿方法,构建了动力学模型与控制策略,仿真结果显示挠度补偿系统能快速有效地抑制挠度造成的轨迹误差．FSW机器人样机焊接实验表明,所提出的机器人在重载作业中能实现高精度的轨迹控制．     

Efficiency evaluation of robots in machining applications using industrial performance measure

The paper is devoted to the robotic based machining. The main focus is made on robot accuracy in milling operation and evaluation robot capacity to perform the task with desired precision. Particular attention is paid to the proper modeling of manipulator stiffness properties and the cutting force estimation. In contrast to other works, the robot performance is evaluated using the circularity norm that evaluates the contortion degree of the benchmark circle to be machined. The developed approach is applied to five industrial robots of KUKA family, which have been ranked for several machining tasks. The validity of the proposed technique was confirmed by experimental study dealing with robot-based machining of circular grooves for several workpiece samples and different locations.     

Study on stiffness visualization and safety control based on will-consensus building for tele-palpation robot system

This paper proposes a method for visualizing the stiffness of a soft object in a palpation-support information system by the teleoperation of a robot hand. It is important that a palpation system display a body’s shape and stiffness. In our method, the stiffness of the contact area between the soft object and the robot finger is estimated by a recursive least-squares method with forgetting factor that uses an impedance dynamics model. With the estimated stiffness and direction of contact force, we calculate the scalar parameter for visualization of stiffness. Moreover, we propose a safety control method for the palpation system, which is part of a tele-control method based on will-consensus building. The system configuration, estimated algorithm, and experimental results are presented.