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 closed-loop error compensation method for robotic flank milling

Errors of diverse sources prevented industrial robots from being adopted into milling applications. This paper proposes a closed-loop error compensation method for robotic flank milling of complex shaped surfaces. First, the finished surface is measured in situ by a laser tracker based measuring system without unclamping the fixture. Then, the sampled points are mapped into the model reference coordinate system and a deterministic bicubic B-spline surface is fitted to extract the systematic components of the machining errors. Finally, the compensation tool path is directly generated for the mirror symmetry points of the only-systematic-error-contained sample points. The robot motion program is converted accordingly for further machining. The experiment shows that the surface accuracy is improved significantly in terms of the profile error via the proposed error compensation process, which well validates the effectiveness of the method.     

工业机器人加工轨迹双目3D激光扫描成像修正方法

为了提高工业机器人作业柔性,本文提出了一种基于双目CCD激光扫描3D成像的“眼在外”(Eye-to-hand:ETH)工业机器人末端(tool center point, TCP)运动轨迹在线修正方法。以激光切割机器人视觉引导为研究背景,降低加工过程机器人对物理工装定位精度的依赖。首先,为提高机器人视觉控制精度,研究了目标工件双目3D激光扫描成像空间点云坐标精确提取方法;其次,融合ETH控制特点和扫描成像系统结构,建立了一种机器人TCP运动轨迹相对偏差在线补偿方法,并通过实验验证了所提方法的可行性,为工业应用奠定基础。     

Integrated approach to robotic machining with macro/micro-actuation

A novel integrated approach to high-accuracy machining with industrial robots is presented in this paper. By combining a conventional industrial robot with an external compensation mechanism, a significantly higher bandwidth of the control of the relative position between the tool and the workpiece can be achieved. A model-based feedback controller for the compensation mechanism, as well as a mid-ranging control architecture for the combined system with the robot and the compensation mechanism are developed. The system performance is evaluated in extensive machining experiments, and the workpiece accuracies achieved are quantified and compared to the corresponding results obtained with state-of-the-art approaches to robotic machining. It is shown that the proposed approach to machining offers significantly higher accuracy, up to eight times improvement for milling in steel, where the required process forces, and thus the exhibited position deviations of the robot, are significant.     

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.     

Enhancement and evaluation in path accuracy of industrial robot for complex surface grinding

Lower path accuracy is an obstacle to the application of industrial robots in intelligent and precision grinding complex surfaces. This paper proposes a novel path accuracy enhancement strategy and different evaluation methods for a six-degree-of-freedom industrial robot FANUC M710ic/50 used for grinding an aero-engine blade. Six groups of theoretical tool paths individually planned on this complex surface were obtained using the iso-parametric method and the constant chord height method. Then the actual paths of the robot were dynamically recorded by a laser tracker with a high frequency. A revised Levenberg-Marquardt and Differential Evolution hybrid algorithm was proposed to improve the absolute robotic positioning accuracy by considering the average curvature variation rate, the arc length and the number of cutter contact points on planning paths. The results showed that the maximum positioning error had been drastically reduced from 0.792 mm to 0.027 mm. Based on the redefinition of robotic path accuracy, including position accuracy and shape accuracy in this work, the methods MP-TLD, BP-TPD and MP-TID were proposed to evaluate the enhanced path accuracy. The evaluation results showed that the different path planning methods have almost little effect on path accuracy. Furthermore, the maximum path deviation evaluated by the MP-TLD method was reduced from 0.378 mm to 0.044 mm, evaluated by the BP-TPD method was reduced from 0.374 mm to 0.029 mm, and evaluated by the MP-TID method was reduced from 0.205 mm to 0.026 mm. It is concluded that these evaluation methods are basically valid and the average path accuracy value is about 0.035 mm, for present complex surface grinding with this typical industrial robot. Finally, the robotic grinding experiments of titanium alloy blades are conducted to further validate the effectiveness of the proposed method.     

Flexible robotic demanufacturing using real time tool path generation

The need for new demanufacturing technologies exists due to a growing population of end of life electronic products. The demanufacturing method presented in this work is unique from disassembly because destructive methods are employed; thus, eliminating the need to account for precedence relationships. Furthermore, the new demanufacturing method employs cutting operations but differs from traditional machining operations due to the degree of flexibility required. To address this very high scale flexibility, a unique prototype flexible demanufacturing work cell has been established. Unique contributions of this flexible demanufacturing method include a new system model that utilizes a product surface model and a robot tool position model to actively generate real time tool paths. The model uses manifolds to reduce the tool path generation function to navigation of the surface manifold. Tool path generation occurs in three stages: machining operation sequencing, active tool path generation and active product avoidance. A case study of the demanufacture of mobile phones is presented to illustrate the flexible robotic demanufacturing operation. The case study shows that a new flexible robotic demanufacturing process has been achieved that requires no predetermined information on the product surface geometry.     

Collision-free and smooth joint motion planning for six-axis industrial robots by redundancy optimization

Planning collision-free and smooth joint motion is crucial in robotic applications, such as welding, milling, and laser cutting. Kinematic redundancy exists when a six-axis industrial robot performs five-dimensional tasks, and there are infinite joint configurations for a six-axis industrial robot to realize a cutter location data of the tool path. The robot joint motion can be optimized by taking advantage of the kinematic redundancy, and the collision-free joint motion with minimum joint movement is determined as the optimal. However, most existing redundancy optimization methods do not fully exploit the redundancy of the six-axis industrial robots when they conduct five-dimensional tasks. In this paper, we present an optimization method to solve the problem of inverse kinematics for a six-axis industrial robot to synthesize the joint motion that follows a given tool path, while achieving smoothness and collision-free manipulation. B-spline is applied for the joint configuration interpolation, and the sum of the squares of the first, second, and third derivatives of the B-spline curves are adopted as the smoothness indicators. Besides, the oriented bounding boxes are adopted to simplify the shape of the robot joints, robot links, spindle unit, and fixtures to facilitate collision detections. Dijkstra's shortest path technique and Differential Evolution algorithm are combined to find the optimal joint motion efficiently and avoid getting into a local optimal solution. The proposed algorithm is validated by simulations on two six-axis industrial robots conducting five-axis flank milling tasks respectively.     

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.     

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.     

Investigation on chatter stability of robotic rotary ultrasonic milling

In recent years, industrial robots with higher flexibility and lower cost have become a hot topic in the manufacturing field. In terms of practical machining applications, they are mainly employed in the situations with low cutting forces such as deburring, chamfering and polishing. However, the weak stiffness of robot induces milling chatter easily. Severe chatter not only damages the dimensional accuracy of parts, but also decreases machining efficiency and tool life. Thus, it is urgent to seek a new method to suppress robotic milling chatter. In this paper, robotic rotary ultrasonic milling (RRUM) technology is used to restrict machining vibration. Meantime, an analytical model of stability is developed. Robotic milling system is considered as a three degrees of freedom (3-DOF) model. After that, based on analysis of dynamic chip thickness, a linear force model is developed through defining an angle γ affected by ultrasonic vibration. Then, the semi-discretization method (SDM) is applied to obtain stability lobe diagrams. The analysis result indicates that stability region of RRUM is improved by 133% compared with robotic conventional milling (RCM). Finally, verification experiments are carried out to prove the rationality and effectiveness of these stability lobe diagrams.     

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.     

Prediction of in-process frequency response function and chatter stability considering pose and feedrate in robotic milling

Chatter occurs easily during robotic milling owing to the low structural stiffness of industrial robots and can degrade the machining quality or even cause robot failure. The accurate frequency response function (FRF) of the robot is essential for predicting chatter stability and selecting the appropriate process parameters. However, the FRF of a robot is affected by multiple factors, such as pose, operating state, and external excitation. In this study, an in-process FRF prediction method considering robot pose and feedrate was developed and used to predict chatter stability. Firstly, the static FRFs were obtained from the experimental modal analysis for different robot poses and used to train a Gaussian process regression (GPR) model. Subsequently, the static FRF predicted using GPR and the modal parameters identified by operational modal analysis (OMA) were used to calculate the in-process FRFs of the robot in the operation state. After removing the harmonic components of the vibration signals using a matrix notch filter, OMA was conducted using the least-squares complex frequency. Furthermore, the FRF of the robot was transformed from the robot flange coordinate system into the engagement coordinate system using the kinematics model and the tool path. The dynamic milling model, considering tool and robot modes was used for predicting stability. Finally, the proposed method was demonstrated by time-domain simulation of the robot-tool system and milling tests, and the effects of the running state and feed direction on chatter stability considering robot mode were analyzed.     

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.     

Rapid prediction of posture-dependent FRF of the tool tip in robotic milling

During the robotic milling process, vibration is one of the main factors that affect the machining accuracy and surface quality due to the low stiffness of the robot structure. The robotic milling stability is a function of the frequency response function (FRF) at the tool tip, which is posture-dependent within the workspace. This paper introduces an approach for rapidly predicting the tool tip FRF for industrial robotic milling at any posture. In this method, the models of the one degree-of-freedom (DOF) robot and two DOF robot are extended to a six DOF industrial robot to calculate the FRF at the holder tip based on the FRF acquisition tests at the arranged postures and a standardization process. Considering the coupling effects between the holder and the tool, the tool tip FRF at any posture of the milling robot is calculated using the receptance coupling substructure analysis (RCSA) method. Accordingly, the proposed method is applied to an industrial robot, and the feasibility of this method for predicting the posture-dependent FRF at high frequency in the workspace is validated though the impact tests. Moreover, the stability lobe diagram is calculated and the chatter tests are performed to validate its accuracy. At last, the robot structural modes are observed at the low-frequency dominant modes, whose frequencies are around 10 to 20 Hz.     

Rapid and flexible prototyping through a dual-robot workcell

With the advancement of CAD/CAM and robot technologies, applying robots for rapid prototyping applications has become a growing trend. However, a single robot can only perform limited prototyping tasks. Compared to a single robot, a dual-robot workcell can have greater structure flexibility, production efficiency, and system reliability due to the inherent parallelism and duality of robots. This paper presents the development and implementation of a dual-robot workcell for prototyping of 3D models. First, kinematic models of both robots in the workcell are established. Then, the concepts of five-axis machining configurations, postprocessing, off-line robot path generation and the dual-robot control scheme are presented. Finally, details of cutting experiments are provided to demonstrate the effectiveness of the system. The results show that the proposed dual-robot workcell is flexible and efficient for prototyping complex components in the current industrial environment.     

Economic analysis of robotic operations: A case study of a thermal spraying robot

There is growing interest in the industrial applications of computer-integrated manufacturing (CIM) and robotic technology. The economic analysis methods which are currently available to assess the cost effectiveness of robotic systems are, however, limited. This paper presents a methodology to address this issue. To demonstrate the methodology, a case-study is presented which uses a thermal spraying robot in a rapid tool manufacturing system. The interdependencies between tolerance, robot accuracy, and the probability of a successful spraying operation are demonstrated. The economic effects of using robots in the spraying process are analyzed. Analytical models are developed to estimate the productivity of components without any defects and the improvement in tool life attributable to robotic spraying. The economic analysis method presented in the paper is also applicable to other operations such as robotic assembly and robotic welding.     

NC tool path generation for 5-axis machining of free formed surfaces

This paper presents a tool axis vector approach for machining sculptured surfaces. Such an approach is well suited for highly twisted, rolled, or bent surfaces. The tool paths are generated for a 5-axis milling machine. The proposed approach is based on tilt angle, cutting direction, and a vector normal to the cutting surface. Gouging is avoided by checking the interference between the cutting tool and the part surface. The algorithm also finds maximum path intervals that generate maximum admissible cusp height within the specified tolerance limits. Such an approach minimizes the tool path and machining time. The paper presents an example to illustrate the details of the algorithm.This research was accomplished by funding provided by the Korean Research Foundation under the Faculty Research Abroad Program and by the advice and support of the second author.