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.     

Passive Compliance from Robot Limbs and its Usefulness in Robotic Automation

Robots have been traditionally used as positioning devices without muchregard to external forces experienced by the tool. This has limited furtherpotential applications of robots in automation. Most tasks that remain to beautomated require constrained robot motion and/or involve work done by therobot on the environment. Such tasks require both force and positioncontrol. The ability to control the end-effector compliance is critical tosuccessful force and position control tasks. Although the end-effectorcompliance can be actively controlled through the joint flexibilitiesprovided by the joint servos or by active force sensing, the usefulness ofhaving the minimum passive compliance in addition to active compliancecontrol can improve performance. In surface following, for example, it isnecessary to make the end-point of a robot have the right compliance toprevent jamming. The usefulness of passive compliance has been demonstratedby the use of compliance-devices on the robot end-effector such as theRemote Center Compliance. The natural compliance inherent in light weightand flexible robot structures, however, can be exploited to provide thenecessary passive compliance required.In this paper we present a novel framework for computing the end-effectorcompliance from the compliance offered by the limbs of a serial robot. Theemphasis is on the explanation of the passive end-effector complianceresulting from these structures, and particular attention is given to theuse of these results in the selection of the type of robot for a particulartask. We show examples of end-effector compliances as functions of jointconfigurations for the SCARA- and PUMA-type robots. The joint-configurationdependent end-effector compliance can be used to select the desired robotpose for the performance of a robotic task.     

Stability and joint stiffness analysis of legged robot’s periodic motion driven by McKibben pneumatic actuator

A McKibben-type pneumatic actuator is widely used as a convenient actuator for a robot with a simple actuator model and a simple control method. However, the effect of its characteristics on the stability of robot motion has not been sufficiently discussed. The purpose of our research is to analyze the influence that the various characteristics of a McKibben pneumatic actuator has on the stability of movements generated by the actuator. In this study, we focus on a periodic motion, which is one of the common movements of robots. We introduce a stability criterion for periodic motion similar to our previous work, in which stability of musculo-skeletal system was discussed, and show that the criterion is always satisfied. Next, we focus on a redundancy of air pressure inputs. As one of application of the redundancy, we investigate the joint stiffness of a robot and propose a design procedure of inputs based on a reference period trajectory and the desired joint stiffness. The stability analysis and design of joint stiffness are verified not only through numerical simulations but also through experiments with a developed 1-DOF legged robot.     

Feedrate planning for machining with industrial six-axis robots

Nowadays, the adaptation of industrial robots to carry out high-speed machining operations is strongly required by the manufacturing industry. This new technology machining process demands the improvement of the overall performances of robots to achieve an accuracy level close to that realized by machine-tools. This paper presents a method of trajectory planning adapted for continuous machining by robot. The methodology used is based on a parametric interpolation of the geometry in the operational space. FIR filters properties are exploited to generate the tool feedrate with limited jerk. This planning method is validated experimentally on an industrial robot.     

Drive based damping for robots with secondary encoders

Robot machining is a growing field due to the combination of large working envelope with relatively low investment and operating costs, compared to milling machine. Besides, the flexibility, which robot serial kinematics bring along, makes application of robot machining possible for different use cases. However, an occurring drawback of robot based machining systems is low stiffness compared to milling machines and, thus, poor accuracy and low eigenfrequencies with few damping. By that, robots for machining are prone to vibrations, resulting in poor machining results. In this paper the authors therefore present an approach for damping these vibrations, using state-of-the-art drives. Secondary encoders, which are increasingly available on industrial robots, are applied to detect these vibrations. This presented strategy has already been proven applicable on feed drives in milling machines and is now applied on industrial robots. To do so, the robot's vibrational behavior, like eigenfrequencies and eigenmodes, is examined in the whole workspace via measurements on real robots. Additionally the excitation by the milling process has been examined in relation to the occurring oscillations at the robot structure. The results of these research is adduced to estimate the applicability of this approach. Based on these results simulations are carried out to test the applicability of the damping strategy on industrial robots. As compliance of robots results mostly from gearboxes, simulation is carried out using a rigid-body-flexible-joint model. The simulations show that the dynamic behavior of the robots axes can be influenced in a positive way and vibration of the robots tool center point can be reduced significantly. Based on these findings, it is planned to implement this method on real hardware to perform tests, develop it further and optimize it.     

Hard material small-batch industrial machining robot

Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the development of safe robots for human-robot collaboration and cooperation, the results of this paper provide a solid background for establishing industrial robots for industrial-machining applications in both small- and medium-size enterprises and large industry. The planned short-term and long-term exploitation of the results should significantly increase the future robot usage in the machining operations.     

Design and analysis of a novel variable stiffness actuator based on parallel-assembled-folded serial leaf springs

Variable stiffness actuator (VSA) can significantly improve the dynamic performance of robots and ensure safety in human robot interaction. In this paper, a novel structure-controlled VSA which achieves a lower minimal stiffness while the size and load capacity remain unchanged is introduced. Stiffness variation is implemented by changing the effective length of parallel-assembled-folded serial leaf springs presented in this paper, which makes the adjustment of stiffness easier and driven by an independent motor. A modified analytical model of joint stiffness is built, which takes the gap between leaf springs and rollers into consideration. Experiments prove that the modified model is more accurate comparing with the ideal model which ignores the gap. Further analyses show that the gap can even make serious impacts on leaf spring-based structure-controlled VSA in other performances such as deformability and energy capacity.     

Environmental Adaptive Control of a Snake-like Robot With Variable Stiffness Actuators

This work investigates adaptive stiffness control and motion optimization of a snake-like robot with variable stiffness actuators. The robot can vary its stiffness by controlling magnetorheological fluid(MRF) around actuators. In order to improve the robot's physical stability in complex environments, this work proposes an adaptive stiffness control strategy. This strategy is also useful for the robot to avoid disturbing caused by emergency situations such as collisions. In addition, to obtain optimal stiffness and reduce energy consumption, both torques of actuators and stiffness of the MRF braker are considered and optimized by using an evolutionary optimization algorithm. Simulations and experiments are conducted to verify the proposed adaptive stiffness control and optimization methods for a variable stiffness snake-like robots.     

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.     

Flatness Based Control of an Industrial Robot Joint Using Secondary Encoders

Due to their compliant structure, industrial robots without precision-enhancing measures are only to a limited extent suitable for machining applications. Apart from structural, thermal and bearing deformations, the main cause for compliant structure is backlash of transmission drives. This paper proposes a method to improve trajectory tracking accuracy by using secondary encoders and applying a feedback and a flatness based feed forward control strategy. For this purpose, a novel nonlinear, continuously differentiable dynamical model of a flexible robot joint is presented. The robot joint is modeled as a two-mass oscillator with pose-dependent inertia, nonlinear friction and nonlinear stiffness, including backlash. A flatness based feed forward control is designed to improve the guiding behaviour and a feedback controller, based on secondary encoders, is implemented for disturbance compensation. Using Automatic Differentiation, the nonlinear feed forward controller can be computed in a few microseconds online. Finally, the proposed algorithms are evaluated in simulations and experimentally on a real KUKA Quantec KR300 Ultra SE.     

The Jacobian condition number as a dexterity index in 6R machining robots

The use of robots for machining operations is growing because of their flexibility to perform a broad spectrum of tasks at a lower cost when compared with machine tools. In this paper the Jacobian condition number is used as a performance index intended to make a better use of revolute-jointed six-degree-of-freedom serial robots in five-axis machining. This index is of the kinetostatic type, low-frequency dynamic effects not being relevant to this study. Indeed, dynamic effects can be neglected because, during machining, the robot is not working at high speed, the spindle motion affecting only the structural, high-frequency modes of the system. The condition number is known to be a measure of Jacobian invertibility; it is used here as an index to improve joint-rate distribution. A low condition number is shown to translate into a smoother joint-rate time history.     

Kinematic analysis and error modeling of TAU parallel robot

The TAU robot presents a new configuration of parallel robots with three degrees of freedom. This robotic configuration is well adapted to perform with a high precision and high stiffness within a large working range compared with a serial robot. It has the advantages of both parallel robots and serial robots. In this paper, the kinematic modeling and error modeling are established with all errors considered using Jacobian matrix method for the robot. Meanwhile, a very effective Jacobian approximation method is introduced to calculate the forward kinematic problem instead of Newton–Raphson method. It denotes that a closed form solution can be obtained instead of a numerical solution. A full size Jacobian matrix is used in carrying out error analysis, error budget, and model parameter estimation and identification. Simulation results indicate that both Jacobian matrix and Jacobian approximation method are correct and with a level of accuracy of micron meters. ADAMS's simulation results are used in verifying the established models.     

机器人串联弹性关节驱动器的刚度控制方法

机器人关节的柔顺性在人机协作过程中具有重要作用，然而固定的关节柔性无法满足动态变化的人机协作需求，因此对机器人的关节驱动器提出了具有刚度调节能力的要求.本文采用阿基米德螺旋线平面涡卷弹簧作为机器人关节的柔性元件，并提出一种可用于具有固定刚度的串联弹性驱动器的刚度控制方法.根据关节刚度的定义，将测量得到的弹簧输出端角度用于计算弹簧的输入端转角，使得机器人关节驱动器的等效刚度可以被调整到所期望的大小.该方法以电机位置控制为内环，关节刚度控制为外环，简化了控制器设计，并实现了解耦控制.对所设计的刚度控制器进行了分析.最后在自主设计的单自由度薄型串联弹性驱动器实验平台上进行了刚度调节实验，包括刚度的双向阶跃、零刚度和正弦变化的刚度，实验结果表明关节等效刚度能准确跟踪期望值，验证了该方法的有效性.     

Dynamic visual servo control of a 4-axis joint tool to track image trajectories during machining complex shapes

A large part of the new generation of computer numerical control systems has adopted an architecture based on robotic systems. This architecture improves the implementation of many manufacturing processes in terms of flexibility, efficiency, accuracy and velocity. This paper presents a 4-axis robot tool based on a joint structure whose primary use is to perform complex machining shapes in some non-contact processes. A new dynamic visual controller is proposed in order to control the 4-axis joint structure, where image information is used in the control loop to guide the robot tool in the machining task. In addition, this controller eliminates the chaotic joint behavior which appears during tracking of the quasi-repetitive trajectories required in machining processes. Moreover, this robot tool can be coupled to a manipulator robot in order to form a multi-robot platform for complex manufacturing tasks. Therefore, the robot tool could perform a machining task using a piece grasped from the workspace by a manipulator robot. This manipulator robot could be guided by using visual information given by the robot tool, thereby obtaining an intelligent multi-robot platform controlled by only one camera.     

Optimal target impedance selection of the robot interacting with human

Human–robot interaction is an important issue in robotic researches which is the key in many rehabilitation and robot-assisted therapy applications. Impedance control can properly handle soft interaction of robots with the environment. Optimal target impedance selection can increase the performance of the overall system and guarantee the stability. The target impedance cannot be selected without proper knowledge about the stiffness and inertia parameters of the human. In this paper, a systematic analysis is done to introduce a method to estimate the human stiffness and consequently adjust the robot target stiffness. Then, particle swarm optimization is used to find the damping and inertia parameters of the robot to minimize the peak of the interaction force. Also, no assumption is made for the passivity of the human dynamic. The passivity analysis of the human–robot system is investigated. The novelty of this paper is in introducing a practical approach to select the robot target impedance. Finally, experimental results on a lower limb exoskeleton are provided to validate the proposed approach.     

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.     

Spindle configuration analysis and optimization considering the deformation in robotic machining applications

Robotic machining is an increasing application due to various advantages of robots such as flexibility, maneuverability and competitive cost. For robotic machining, the machining accuracy is the major concern of current researches. And particular attention is paid to the proper modeling of manipulator stiffness properties, the cutting force estimation and the robot posture optimization. However, through our research, the results demonstrate the spindle configuration largely affects the deformation of the robot end-effector (EE). And it may even account for approximately half of the total deformation for machining applications with the force acting perpendicular to the tool. Furthermore, the closer distance between the tool tip and the EE does not mean that the deformation tends to be smaller. Thus, it is reasonable to consider optimizing the spindle configuration based on the optimal robot posture, thereby exhausting advantages of the robot and further reducing machining errors. In this paper, a spindle configuration analysis and optimization method is presented, aiming at confirming the great influence of the spindle configuration on the deformation of the robot EE and minimizing it. First, a deformation model based on the spindle configuration (SC-based deformation model) is presented, which establishes a mapping between the spindle configuration and the deformation of the robot EE. And it confirms the large effect of the spindle configuration on the deformation of the EE. Then, a complementary stiffness evaluation index (CSEI) is proposed. And it adopts matrix norms to evaluate the influence of the spindle configuration on the complementary stiffness matrix in the SC-based deformation model. Using this index, the proposed SC-based deformation model is simplified for the ODG-JLRB20 robot adopted in this paper. Finally, a spindle configuration optimization model is derived to minimize the simplified SC-based deformation model using an iterative procedure. With this model, the optimal spindle configuration with respect to the EE can be obtained for a specific machining trajectory. Experimental results conducted on the ODG-JLRB20 robot demonstrate the correctness and effectiveness of the present method.     

Kinematic Design of Modular Reconfigurable In-Parallel Robots

This paper describes the kinematic design issues of a modular reconfigurable parallel robot. Two types of robot modules, the fixed-dimension joint modules and the variable dimension link modules that can be custom-designed rapidly, are used to facilitate the complex design effort. Module selection and robot configuration enumeration are discussed. The kinematic analysis of modular parallel robots is based on a local frame representation of the Product-Of-Exponentials (POE) formula. Forward displacement analysis algorithms and a workspace visualization scheme are presented for a class of three-legged modular parallel robots. Two three-legged reconfigurable parallel robot configurations are actually built according to the proposed design procedure.     

Modelling the dynamics of industrial robots for milling operations

Using industrial robots as machine tools is targeted by many industries for their lower cost and larger workspace. Nevertheless, performance of industrial robots is limited due to their mechanical structure involving rotational joints with a lower stiffness. As a consequence, vibration instabilities, known as chatter, are more likely to appear in industrial robots than in conventional machine tools. Commonly, chatter is avoided by using stability lobe diagrams to determine the stable combinations of axial depth of cut and spindle speed. Although the computation of stability lobes in conventional machine tools is a well-studied subject, developing them in robotic milling is challenging because of the lack of accurate multi-body dynamics models involving joint compliance able of predicting the posture-dependent dynamics of the robot. In this paper, two multi-body dynamics models of articulated industrial robots suitable for machining applications are presented. The link and rotor inertias along with the joint stiffness and damping parameters of the developed models are identified using a combination of multiple-input multiple-output identification approach, computer-aided design model of the robot, and experimental modal analysis. The performance of the developed models in predicting posture-dependent dynamics of a KUKA KR90 R3100 robotic arm is studied experimentally.     

Shape recovery from robot contour-tracking with force feedback

In this paper we describe a process for shape recovery from robot contour-tracking operations with force feedback. Shape recovery is an important task for self-teaching robots and for exploratory operations in unknown environments. An algorithm which directs a position-controlled robot around an unknown planar contour using the steady-state contact force information is described in this paper. Shape recovery from planar contouring is not a trivial problem. It was found experimentally that there is significant distortion of the original contour if direct kinematics are used to recover the object's shape, as we are unable to recover the exact position of the robot tool owing to the errors present in the kinematic model of the arm and the non-linearities of the drive train. Drive train errors can consist of the joint compliance, gear backlash, and gear eccentricity. A mathematical model of the errors generated by the drive train has been previously addressed. In this paper a compensation process is explored for purposes of planar shape recovery. It was found through experimentation that the joint compliance is most conveniently compensated for in practice. Improvements in the shapes recovered from robot contouring are seen with our compensations. Experimental details and difficulties are also discussed.