Tool Center Point Research Articles

A novel hand-eye calibration method for industrial robot and line laser vision sensor

PurposeThe purpose of this study is solving the hand–eye calibration issue for line structured light vision sensor. Only after hand–eye calibration the sensor measurement data can be applied to robot system.Design/methodology/approachIn this paper, the hand–eye calibration methods are studied, respectively, for eye-in-hand and eye-to-hand. Firstly, the coordinates of the target point in robot system are obtained by tool centre point (TCP), then the robot is controlled to make the sensor measure the target point in multiple poses and the measurement data and pose data are obtained; finally, the sum of squared calibration errors is minimized by the least square method. Furthermore, the missing vector in the process of solving the transformation matrix is obtained by vector operation, and the complete matrix is obtained.FindingsOn this basis, the sensor measurement data can be easily and accurately converted to the robot coordinate system by matrix operation.Originality/valueThis method has no special requirement for robot pose control, and its calibration process is fast and efficient, with high precision and has practical popularized value.

Algebraic Modeling of Cylindrical Interference-Free Power-Skiving Tool for Involute Internal Gear Cutting With Tilt Angle

Abstract The development of feasible methods for the design of power-skiving tools without cutting interference is essential in ensuring the accuracy of involute internal machined gears. One of the most crucial points in obtaining interference-free and resharpenable power-skiving tools is that of determining the cutting-edge and clearance surface. The present study introduces a tilt angle during the power-skiving process to design a simple cylindrical interference-free tool shape, in which the shape of the cutting edge remains unchanged after resharpening. The relative position between the new tool center point and gear during machining is similarly unchanged after resharpening. In addition, the clearance angle between the tool and the gear can be easily adjusted simply by changing the tilt angle of the tool during power-skiving. The validity of the proposed design method is demonstrated through a simple numerical example. The simulation results confirm the feasibility of the proposed method.

Model order reduction via substructuring for a nonlinear, differential‐algebraic machine tool model with moving loads

AbstractMachine tools are permanently exposed to complex static, dynamic and thermic loads. This often results in an undesired displacement of the tool center point (TCP), causing errors in the production process and thus limiting the achievable workpiece quality. Recent research efforts try to counter these effects by process‐parallel solutions utilizing machine internal data. Therefore, fast simulation models are a fundamental requirement. Here, model order reduction (MOR) becomes crucial. The resulting low‐dimensional models are required for various applications, e.g., in digital twins, the correction of thermally induced errors at the TCP during the production process as well as for lifetime calculations in predictive maintenance. In this contribution, we present a strategy of MOR for a coupled thermo‐mechanical model with a nonlinear subsystem and moving loads, using the example of a feed axis with nonlinear machine components. Applying tailored substructuring techniques, we are able to separate the linear and nonlinear system components. This allows to apply classic linear MOR methods to the much larger linear part, whereas the small nonlinear part is kept, and thus enables drastically reduced computing times. The relative movement is considered by a switched system approach. Transient thermo‐mechanical interactions of the feed axis are calculated in a final investigation, comparing the performance of the resulting reduced‐order model and the original one.

Optimal design for compliance modeling of industrial robots with bayesian inference of stiffnesses

In this paper a cost and time efficient approach to setup a compliance model for industrial robots is presented. The compliance model is distinctly determined by the gear’s stiffness parameters which are tuned by an optimal design of experiments approach. The experimental setup consists of different poses of the robot’s axes together with the applied force at the tool center point (TCP). These robot poses represent together with defined forces the experimental setup where the deviation of the robot under defined force is measured. Based on measurements of the displacement of the TCP the stiffness parameters for the compliance model are estimated and afterwards validated in new experiments. The efficiency of this approach lies in the reduced amount of experiments that are needed to identify the stiffness parameters that are parameters inherent to the compliance and the less complex experimental setup.

Force-based control strategy for a collaborative robotic camera holder in laparoscopic surgery using pivoting motion.

Introduction: Laparoscopic surgery often relies on a fixed Remote Center of Motion (RCM) for robot mobility control, which assumes that the patient's abdominal walls are immobile. However, this assumption is inaccurate, especially in collaborative surgical environments. In this paper, we present a force-based strategy for the mobility of a robotic camera-holder system for laparoscopic surgery based on a pivoting motion. This strategy re-conceptualizes the conventional mobility control paradigm of surgical robotics. Methods: The proposed strategy involves direct control of the Tool Center Point's (TCP) position and orientation without any constraints associated with the spatial position of the incision. It is based on pivoting motions to minimize contact forces between the abdominal walls and the laparoscope. The control directly relates the measured force and angular velocity of the laparoscope, resulting in the reallocation of the trocar, whose position becomes a consequence of the natural accommodation allowed by this pivoting. Results: The effectiveness and safety of the proposed control were evaluated through a series of experiments. The experiments showed that the control was able to minimize an external force of 9N to ±0.2N in 0.7s and reduce it to 2N in just 0.3s. Furthermore, the camera was able to track a region of interest by displacing the TCP as desired, leveraging the strategy's property that dynamically constrains its orientation. Discussion: The proposed control strategy has proven to be effective minimizing the risk caused by sudden high forces resulting from accidents and maintaining the field of view despite any movements in the surgical environment, such as physiological movements of the patient or undesired movements of other surgical instruments. This control strategy can be implemented for laparoscopic robots without mechanical RCMs, as well as commercial collaborative robots, thereby improving the safety of surgical interventions in collaborative environments.

A multiple test arbors-based calibration method for a hybrid machine tool

Kinematic calibration is a necessary way to guarantee the accuracy of hybrid machine tools. The traditional calibration methods have high requirements for the measuring instruments and the measurement environment, and the measurement is extremely complex. The contradiction between measurement complexity and identification accuracy is an important problem in calibration. In this paper, a multiple test arbors-based calibration method for a hybrid machine tool is presented. The tool center point (TCP) position errors of multiple test arbors are measured sequentially by virtual TCP position constraints. The error parameters can be accurately identified based on these position errors without orientation measurement. The corresponding measurement scheme is described in detail according to whether the ball diameters of the test arbors are the same. The influence of the length and number of test arbors on the calibration results is investigated, and the basic principle for the selection of test arbors is given. Finally, the proposed method is validated by simulations and experiments. The proposed method can achieve overall high-accuracy calibration with simple measurement devices and convenient measurement steps, which provides a basis for automated calibration.

A prediction and compensation method of robot tracking error considering pose-dependent load decomposition

Industrial robots are widely used because of their high flexibility and low cost compared with CNC machine tools, but the low tracking accuracy limits their application in the field of high-precision manufacturing. To improve the tracking accuracy and solve the complex modeling problems, a prediction and compensation method of robot tracking error is proposed based on temporal convolutional network (TCN), where the pose-dependent effect of load on joint tracking error is considered. The terminal load is decomposed to joint load by using Jacobian matrix and then used as the pose-dependent information of the data-based model. A prediction model based on TCN is used to predict the tracking error of joints. Finally, a pre-compensation method is adopted to improve the joint tracking accuracy based on the predicted errors. Experimental results show that the model presents good prediction and compensation accuracy. The mean absolute tracking errors are increased by more than 80% in the test path. This method can effectively compensate the tracking errors of the robot joints and therefore greatly improve the tracking accuracy of the tool center point and tool orientation in the Cartesian coordinate system.

Model-based feed rate optimization for cycle time reduction in milling

Feed rate is an important determinant of the cutting force and cycle time. Selection of an appropriate feed rate can increase the processing quality and production efficiency. To determine an optimized feed rate, many methods have been developed to maintain a constant cutting force by applying a real-time feedback system constructed with data such as the tool condition, temperature, and cutting load of the spindle. However, these methods have low reliability because of difficulty in accurately measuring the spindle load. Moreover, real-time changes in the feed rate alter the cycle time. This study optimized the feed rate to a value that maintains the cutting force based on a cutting force prediction model and an algorithm to extract the cutting conditions from each line of the G-code. The feed rate optimization was applied to a flat end mill and ball end mill. An interpreter for the G-code was configured to calculate the tool center point and cutting condition. A real-time spindle power measurement system was constructed to measure the cutting force in each line of the G-code by identifying the parameters of the cutting force prediction model. The cutting force criterion was selected as the highest value among the predicted cutting forces. The optimized feed rate that maintains the cutting force was extracted based on the cutting conditions in other lines and the cutting force prediction model. The extracted feed rate was applied to the G-code by modifying only the feed rate command. Experimental results obtained with a commercial machining tool show that the proposed feed rate optimization significantly reduces the overall cycle time and effectively maintains the cutting force.

Calibration procedure and biomechanical validation of an universal six degree-of-freedom robotic system for hip joint testing

PurposeAmong various test methods for different human joints, the use of robot systems has attracted major interest and inherits the potential to become a gold standard in biomechanical testing in the future. A key issue associated with those robot-based platforms is the accurate definition of parameters, e.g., tool center point (TCP), length of tool or anatomical trajectories of movements. These must be precisely correlated to the physiological parameters of the examined joint and its corresponding bones. Exemplified for the human hip joint, we are creating an accurate calibration procedure for a universal testing platform by using a six degree-of-freedom (6 DOF) robot and optical tracking system for recognition of anatomical movements of the bone samples.MethodsA six degree-of-freedom robot (TX 200, Stäubli) has been installed and configured. The physiological range of motion of the hip joint composed of a femur and a hemipelvis was recorded with an optical 3D movement and deformation analysis system (ARAMIS, GOM GmbH). The recorded measurements were processed by automatic transformation procedure (created in Delphi software) and evaluated in 3D CAD system.ResultsThe physiological ranges of motion were reproduced for all degrees of freedom with the six degree-of-freedom robot in adequate accuracy. With the establishment of a special calibration procedure by using a combination of different coordinate systems, we were able to achieve a standard deviation of the TCP depending of the axis between 0.3 and 0.9 mm and for the length of tool between + 0.67 and − 0.40 mm (3D CAD processing) resp. + 0.72 mm to − 0.13 mm (Delphi transformation). The accuracy between the manual and robotic movement of the hip shows an average deviation between − 0.36 and + 3.44 mm for the points on the movement trajectories.ConclusionA six degree-of-freedom robot is appropriate to reproduce the physiological range of motion of the hip joint. The described calibration procedure is universal and can be used for hip joint biomechanical tests allowing to apply clinically relevant forces and investigate testing stability of reconstructive osteosynthesis implant/endoprosthetic fixations, regardless of the length of the femur, size of the femoral head and acetabulum or whether the entire pelvis or only the hemipelvis will be used.

Automatic Calibration of Tool Center Point for Six Degree of Freedom Robot

The traditional tool center point (TCP) calibration method requires the operator to use their experience to set the actual position of the tool center point. To address this lengthy workflow and low accuracy, while improving accuracy and efficiency for time-saving and non-contact calibration, this paper proposes an enhanced automatic TCP calibration method based on a laser displacement sensor and implemented on a cooperative robot with six degrees of freedom. During the calibration process, the robot arm will move a certain distance along the X and Y axes and collect the information when the tool passes through the laser during the process to calculate the runout of the tool, and then continue to move a certain distance along the X and Y axes for the second height calibration. After the runout angle is calculated and calibrated by triangulation, the runout calibration is completed and the third X and Y axis displacement is performed to find out the exact position of the tool on the X and Y axes. Finally, the tool is moved to a position higher than the laser, and the laser is triggered by moving downward to obtain information to complete the whole experimental process and receive the calibrated tool center position. The whole calibration method is, firstly, verified in the virtual simulation environment and then implemented on the actual cooperative robot. The results of the proposed TCP calibration method for the case of using a pin tool can achieve a positioning deviation of 0.074 and 0.125 mm for the robot moving speeds of 20 and 40 mm/s, respectively. The orientation deviation in the x-axis are 0.089 and −0.184 degrees for the robot moving speeds of 20 and 40 mm/s, respectively. The positioning repeatability of ±0.083 mm for the moving speed of 20 mm/s is lower than ±0.101 mm for the speed of 40 mm/s. It shows that lower moving speed can obtain higher accuracy and better repeatability. This result meets the requirements of TCP calibration but also achieves the purpose of being simple, economical, and time-saving, and it takes only 60 s to complete the whole calibration process.

Error Similarity Analysis and Error Compensation of Industrial Robots with Uncertainties of TCP Calibration

The machining system based on an industrial robot is a new type of equipment to meet the requirements of high quality, high efficiency and high flexibility for large and complex components of aircraft and spacecraft. The error compensation technology is widely used in robotic machining to improve the positioning accuracy of an industrial robot with the intention of meeting the precision requirements of aerospace manufacturing. However, the robot’s positioning accuracy decreases significantly when the orientation of the tool changes dramatically. This stems from the fact that the existing robot compensation methods ignore the uncertainties of Tool Center Point (TCP) calibration. This paper presents a novel regionalized compensation method for improving the positioning accuracy of the robot with calibration uncertainties and large orientation variation of the TCP. The method is experimentally validated through the drilling of curved surface parts of plexiglass using a KUKA KR2830MT robot. Compared with a published error compensation method, the proposed approach improves the positioning accuracy of the robot under the large orientation variation to 0.235 mm. This research can broaden the field of robot calibration technology and further improve the adaptability of robotic machining.

Decomposition of trajectory errors caused by flexibility outside the control loop based on the frequency-domain machine tool mechatronics model

Under high-speed and high-acceleration conditions, flexibility outside the control loop (FOCL) is one of the critical incentives for trajectory errors (TEs). Because the FOCL will deform and vibrate under the action of inertial forces, which leads to TEs. FOCL contains multiple components, and the contribution of each component to TE needs to be evaluated. This paper first proposes a frequency domain dynamic model-based multi-axis machine tool trajectory tracking simulation method and a FOCL-induced TE decomposition method. Then using the proposed methods, quantitatively evaluates the contribution of different components of FOCL to TE caused by FOCL and discusses the dominant influencing factors. The mechatronics model of the machine tool is established in the frequency domain. This allows the lead screw to be equivalent to the spectral beam element, which is generated using the exact solution of the governing differential equations and can describe the lead screw’s higher-order dynamics with fewer degrees of freedom. The TE of the test trajectory is calculated using a setpoint-trajectory-based numerical method. Using this method, the calculated TEs have the same reference and can be directly subtracted to achieve TE separation. Hence, the decomposition of TE caused by FOCL can be achieved by further calculating the TE of the tool center point (TCP) trajectory that only considers part of the FOCL components and subtracting it from the TE of the feedback trajectory.

A novel hand-eye calibration method of picking robot based on TOF camera.

Aiming at the stability of hand-eye calibration in fruit picking scene, a simple hand-eye calibration method for picking robot based on optimization combined with TOF (Time of Flight) camera is proposed. This method needs to fix the TOF depth camera at actual and calculated coordinates of the peach the end of the robot, operate the robot to take pictures of the calibration board from different poses, and record the current photographing poses to ensure that each group of pictures is clear and complete, so as to use the TOF depth camera to image the calibration board. Obtain multiple sets of calibration board depth maps and corresponding point cloud data, that is, "eye" data. Through the circle center extraction and positioning algorithm, the circle center points on each group of calibration plates are extracted, and a circle center sorting method based on the vector angle and the center of mass coordinates is designed to solve the circle center caused by factors such as mirror distortion, uneven illumination and different photographing poses. And through the tool center point of the actuator, the coordinate value of the circle center point on the four corners of each group of calibration plates in the robot end coordinate system is located in turn, and the "hand" data is obtained. Combined with the SVD method, And according to the obtained point residuals, the weight coefficients of the marker points are redistributed, and the hand-eye parameters are iteratively optimized, which improves the accuracy and stability of the hand-eye calibration. the method proposed in this paper has a better ability to locate the gross error under the environment of large gross errors. In order to verify the feasibility of the hand-eye calibration method, the indoor picking experiment was simulated, and the peaches were identified and positioned by combining deep learning and 3D vision to verify the proposed hand-eye calibration method. The JAKA six-axis robot and TuYang depth camera are used to build the experimental platform. The experimental results show that the method is simple to operate, has good stability, and the calibration plate is easy to manufacture and low in cost. work accuracy requirements.

Influence of lateral dynamic error on the trajectory error in machine tools

In machine tools, the trajectory error of the tool center point (TCP) is caused due to the dynamic positioning error of feed drive systems according to the relationship in spatial structure and motion. The dynamic positioning error of the feed drive system includes axial dynamic error and lateral dynamic error. To analyze the influence of the lateral dynamic error on the trajectory error of the TCP of multi-axis machine tools, in this study, circular and butterfly trajectories were designed as the set trajectories of a machine tool with three linear axes. In addition, the tracking error models were constructed both considering the lateral dynamic error and without considering the lateral dynamic error, and the difference between the two models was quantified. The Sobol method was then used to analyze the sensitivity of the lateral dynamic error of the feed drive system to the tracking error of the TCP. Finally, experiments were performed on a three-axis machine tool. The results show the maximum lateral dynamic error in the direction perpendicular to the motion direction is 0.026 mm. The lateral dynamic error detrimentally affects the tracking error and contour error of the TCP in multi-axis machine tools.

A review on epoxy granite reinforced polymer composites in machine tool structures – Static, dynamic and thermal characteristics

AbstractMachine tool structures produced with Epoxy Granite reinforced polymer composites (EGPCs) have gained prominence in recent years and have replaced conventional cast iron materials and other metals due to its remarkable damping characteristics. However, machine tool structures manufactured with EGPCs tends to exhibit limited strength, stiffness and stability. Such challenges in EGPCs are resolved by incorporation of steel as additional reinforcement and enhanced mechanical properties are observed in these hybrid machine‐tool structures. Hybrid epoxy granite machine tool structures with enhanced mechanical performance are prone to thermal errors resulting in machining inaccuracies and limited performance. Thermal errors induced in machine tool structures could be attributed due to effect of temperature distribution and displacements at the Tool Center Point (TCP). This review work carried out focuses predominantly on design methods adopted in resolving the challenges identified in development of machine tool structures and further analyses results of several polymer concrete‐based machine tool structures with regard to static, dynamic and thermal characteristics. Several review works conducted earlier have discussed the results of static and dynamic characteristics, whereas this review work provides additional information on thermal based errors induced and discusses the methods adopted in compensation of thermal errors. In this review paper, research studies pertaining to static and dynamic characteristics of different machine tool structures performed in last three decades have been discussed and a wholistic information is provided in relation with static, dynamic and thermal characteristics and properties toward developing a machine tool structure with a novel, newer class or alternative materials.

Generation of Configuration Space Trajectories Over Semi-Constrained Cartesian Paths for Robotic Manipulators

Serial-link manipulators are required to execute trajectories that enable a robot end-effector or a tool to track a Cartesian path. Practical applications may not require constraining all six degrees of freedom (position and orientation) of the tool resulting in semi-constrained paths. Semi-constrained paths allow improved success rates and better quality trajectories as the robot has more freedom to meet the kinematic and dynamic constraints. Additionally, robotic applications will need to use multiple tool center points (TCPs) on the tool to generate feasible paths for the robot. We present an iterative graph construction method to find trajectories for semi-constrained Cartesian paths that also use multiple TCPs. Our graph-based method finds multiple inverse kinematic solutions for possible Cartesian poses that the robot can take and connects them to build a graph. The algorithm uses cues from the Cartesian space to prioritize poses that produce a better quality solution. A biasing scheme is also developed to selectively sample the starting Cartesian poses from available choices. Our method finds near-optimal solutions with significantly fewer nodes and edges in the graph. The algorithm’s performance results on complex industrial test cases are provided. Note to Practitioners—Industrial applications permit the relaxation of one or more degrees of freedom of the tool while following the Cartesian paths. The relaxation of constraints is introduced by defining tolerances between the tool and the workpiece. Multiple TCPs have to be employed for many tasks to use different surfaces of the tool. In this paper, we present a planning algorithm for semi-constrained Cartesian paths that can incorporate the use of multiple TCPs. The user can define discrete TCPs over the tool contact points or surfaces. The tolerances can be easily defined as angular limits on tool orientation along the Cartesian path. Our planning algorithm can work with others via point constraints in Cartesian space or joint space of the robot. Practitioners from the industry can use the method presented in this paper to develop automated robotic cells that do cutting, sanding, polishing, welding, painting, composite layup, additive manufacturing, and several other common applications.

Virtual sensor for monitoring the geometric and kinematic accuracy of machine tools

The performance of machine tools depends on their working accuracy. The paper presents a new approach for in-process monitoring the geometric and kinematic accuracy of a machine tools. This approach utilizes a virtual sensor for capturing displacements at the tool center point (TCP). The virtual sensor is set up by using a data-driven approach based on extended transmissibility functions. The input data for monitoring are the NC internal data. The transmissibility functions are established via standard experimental procedures such as double ball bar (DBB) tests tests and estimation of frequency response functions (FRF). The data from the virtual sensor can be used for process monitoring and troubleshooting when launching a new process.

Accurate TCP Position and Orientation Trajectory Generation in 6DOF Robotic Manipulators and CNC Machine Tools using FIR Filtering and Haversine Synchronisation

The use of robotics in manufacturing is rapidly growing. One promising application in particular is the use of robots as machining platforms. Robotic machining offers many advantages such as large operating envelopes, flexibility in operations and low installation and running costs. Robotic machining platforms much like computer numerically controlled (CNC) machine tools are commanded by numerical controllers (NCs) using the well established G-code part programming language (ISO-6983). Toolpaths are defined in the work piece coordinate system (WCS) as a series of discrete tool centre point (TCP) positions and tool orientations. The role of the NC is to generate smooth feed drive or robot joint commands such that the tool or end effector travels along the commanded toolpath whilst satisfying TCP position and orientation tolerances and robot/machine tool kinematic constraints. Interpolating tool orientations directly in the WCS requires complex real-time spherical interpolation computations. Overcoming this challenge, this paper introduces a C4 continuous tool path trajectory generation method for 6DOF motion. The tool centre point position is smoothed in the WCS, however, the tool orientation is smoothed directly in the rotary coordinate system without the requirement for spherical interpolation. The interpolated tool orientation trajectory follows the path of the great circle arc using the modified Haversine method eliminating non-linear interpolation errors present in linear interpolation of rotary axis positions (machine coordinate system interpolation). The proposed method is validated by simulation of a 6DOF robotic manipulator.

Bio-based insulation materials and model predictive control of active cooling systems in machine tools

The adoption of biological principles and materials plays a decisive role in the conversion to sustainable production technologies. Measures for the biological transformation of a machine tool were implemented following the example of warm-blooded animal, which automatically control their core temperature and, depending on their habitat, possess an insulating layer of fat. In this work, thermal insulation measures were implemented on machine tools using renewable materials and their effects were evaluated.Insulation materials of petrochemical origin such as polystyrene (Styrofoam) were replaced by alternatives made of mycelium with comparable heat insulating properties. On the lower machine bed, a slowdown of the cooling rate was observed after application of insulation materials at external temperature drops. The insulation between the machine bed and the control cabinet was also found to reduce tool centre point (TCP) displacement. This cost-efficient measure reduces the error during the process and the effort required to correct the linear axes and to heat and cool the machine.To homogenize the temporal and spatial temperature profile of machine tools, a control system was developed to compensate for thermally induced errors by means of adaptive active cooling. Therefore, a model predictive control using an embedded artificial intelligence (AI) model to forecast the structural temperature development was implemented. Through a hybrid training database combining experimental and simulative data series, a both flexible and precise determination of the thermal system behaviour could be achieved. On a real production machine, the active cooling system is divided into five individually controllable and adjustable cooling circuits. This approach allows cooling the machine structure according to time and local demand to minimize thermally induced TCP displacement under variable operating conditions.This paper serves to define and evaluate possibilities and requirements for the integration of bio-based insulation materials and control algorithms for homoiothermic conditions in production machines.

High Precision Calibration for Three-Dimensional Vision-Guided Robot System

Calibration is an important premise for vision-guided robot system, especially for precise industrial operations on curved surfaces. Most of existing methods focus on one or partial union of errors including assembly error of the robot, relative pose error between the vision unit and the robot, or installation error of end effector, which is still challenging in practice. To solve this problem, this article proposes a new calibration method based on error correction matrix by which different manifestations of each error is unified. As the nonlinear equations formed by these matrices cannot be solved analytically, a numerical optimization solution based on Lie algebra is presented. Specifically, the matrices acquisition is formulated as the problem of minimizing the sum of distance deviations between actual and ideal tool center points. This problem is then solved by differentiating these matrices with a form of left multiplicative perturbation. In this way, a high precision joint calibration with multisource errors is achieved. The proposed method is verified by simulations and experiments.