High-precision Robot Research Articles

Error analysis of a coaxis five-bar parallel mechanism

Abstract With societal advancement, robots are increasingly being deployed in production processes. Currently, high-precision robots predominantly found in the market are delta parallel robots. Common parallel robots, including delta robots, generally suffer from the drawback of having a smaller workspace compared to serial robots. Contrasted with other types of parallel robots, coaxis parallel robots feature a larger workspace, thereby offering greater potential for application. This paper focuses on a coaxis five-bar parallel mechanism as the subject of investigation. Firstly, by employing the perturbation method to model the errors in the parallel mechanism, a mapping relationship between error sources and the errors of the mechanism’s end-effector was derived. Then a sensitivity analysis of each error source was performed statistically, yielding sensitivity metrics. Last, under conditions where the magnitudes of errors are identical, the end-effector error of a coaxis parallel mechanism is notably larger compared to that of a common parallel mechanism. This makes it more essential to conduct precision design on coaxis parallel robots in the future study.

An online prediction and compensation method for robot position errors embedded with error-motion correlation

Error prediction and compensation are crucial requirements for improving robot accuracy. To this end, this paper introduces an advanced online method that integrates error-motion correlation for the precise prediction and compensation of robot position errors. The proposed method includes feature selection, model interpretability design, and compensation value smoothness. Analyzing the error characteristics and designing a model based on error-motion correlation reveals that the proposed method reduces position errors by 92 % and 89 % at a frequency of 250 Hz in two tasks with different working conditions. This reduction in position errors ensures smoother compensation, leading to a notable improvement in accuracy for high-precision robotics applications. Unlike existing research that focuses on mapping models, the proposed method prioritizes understanding error behavior, thereby resulting in a comprehensive approach for error management in robotic systems. This contribution is invaluable for advancing the field of precision robotics and ensuring reliable performances in various robotic tasks.

A New Calculation Method for Instantaneous Efficiency and Torque Fluctuation of Spur Gears

As a critical component of the joint gearbox, spur gear pairs play a crucial role in energy conversion, limiting the performance of a collaborative robot. Accurately assessing their instantaneous efficiency and torque fluctuation is essential for developing high-precision robot joint control models. This study proposes a computational model to predict the instantaneous efficiency and torque fluctuation of spur gears under typical operating conditions. The model incorporates a torque balance model, a load distribution model, and a friction model to reflect the relationship between gear meshing position and efficiency. The instantaneous efficiency and torque fluctuation of gear pairs were compared with the Coulomb friction model with an average friction coefficient and the elastohydrodynamic lubrication model with a time-varying friction coefficient. The effect of gear contact ratio on efficiency is analysed, while the instantaneous efficiency and torque fluctuation of gears are studied under varying operating conditions. The results indicate a maximum efficiency difference of 1.86 % between the two friction coefficient models. Under specific operating conditions, the instantaneous efficiency variation of the gear pair can reach 3.34 %, and the torque fluctuation can reach 5.19 Nm. Finally, this study demonstrates the effectiveness and accuracy of the proposed method through comparative analysis.

Robotic Disassembly Task Training and Skill Transfer Using Reinforcement Learning

This paper proposes a platform for robots to learn disassembly tasks based on reinforcement learning (RL) techniques. The platform is demonstrated by a robot learning the skill of removing a bolt along a door-chain groove in a data-driven way, where the clearance between the bolt and the groove is less than 1mm. Furthermore, the relationship between the performance of the learned skills and the precision of the robot is studied with a method to control the robot's precision by adding uncorrelated zero-mean Gaussian noise to the robot's actions. Finally, the transferability of the learned skills among robots with different precisions is empirically studied. It has been found that skills learned by a low-precision robot can perform better on a robot with higher precision, and skills learned by a high-precision robot have worse performance on robots with lower precision.

Design and implementation of an adaptive neural network observer–based backstepping sliding mode controller for robot manipulators

Robot manipulators as an indispensable part of automatic operation are becoming increasingly important in intelligent manufacturing systems, such as grinding and assembly. Although control methods of robot manipulators have been extensively studied, high-precision robots still face new challenges from uncertainties caused by changes in the environment and enhancement of interference. As a consequence, the neural network-based observer is utilized to reduce the influence of uncertainties and external disturbances. In this work, a new kind of nonlinear disturbance observer is designed which could well function with observed states. To improve the control efficiency and response characteristic, a kind of new integral sliding manifold is devised and the control input is generated via backstepping techniques. The stability is proved with Lyapunov theory, and the experimental results are given to demonstrate the effectiveness of the proposed controller.

MRI-compatible electromagnetic servomotor for image-guided medical robotics

The soft-tissue imaging capabilities of magnetic resonance imaging (MRI) combined with high precision robotics has the potential to improve the precision and safety of a wide range of image-guided medical procedures. However, functional MRI-compatible robotics have not yet been realized in part because conventional electromagnetic servomotors can become dangerous projectiles near the strong magnetic field of an MRI scanner. Here we report an electromagnetic servomotor constructed from non-magnetic components, where high-torque and controlled rotary actuation is produced via interaction between electrical current in the servomotor armature and the magnetic field generated by the superconducting magnet of the MRI scanner itself. Using this servomotor design, we then build and test an MRI-compatible robot which can achieve the linear forces required to insert a large-diameter biopsy instrument in tissue during simultaneous MRI. Our electromagnetic servomotor can be safely operated (while imaging) in the patient area of a 3 Tesla clinical MRI scanner.

Diagnosis of the Misaligned Faults of the Vertical Test Instrument of High-Precision Industrial Robot Reducer

High-precision reducer is the core component of industrial robots. In order to achieve the comprehensive performance testing of precision reducers, an instrument with a vertical layout and a cylindrical structure is designed. As a rotating machine, the inevitable coupling misalignment of the instrument can lead to vibration faults which lead to errors in the test. So it is pretty necessary to diagnose and monitor the coupling misalignment while the instrument is working. The causes of the coupling misaligned fault of the instrument and the relationship between the misalignment fault and torque ripple are analyzed in this paper. A method of using the torque transducer in the measurement chain of the instrument to diagnose the coupling misalignment is proposed in this paper. Many experiments have been done to test the capability of detecting the coupling misalignment using this method. Experimental results show that the amplitude of torque ripple of the shaft is linearly related to the coupling misalignment and is quadratically related to the rotation speed of the shaft when the misalignment exists in the shaft. The combination of components at the rotation frequency (fr) and the additional components can be used to diagnose faults due to coupling misalignment.

High-precision robotic assembly system using three-dimensional vision

The design of a high-precision robot assembly system is a great challenge. In this article, a robotic assembly system is developed to assemble two components with six degree-of-freedoms in three-dimensional space. It consists of two manipulators, a structured light camera which is mounted on the end-effector aside component A to measure the pose of component B. Firstly, the features of irregular components are extracted based on U-NET network training with few labeled images. Secondly, an algorithm is proposed to calculate the pose of component B based on the image features and the corresponding three-dimensional coordinates on its ellipse surface. Thirdly, the six errors including two position errors and one orientation error in image space, and one position error and two orientation errors in Cartesian space are computed to control the motions of component A to align with component B. The hybrid visual servoing method is used in the control system. The experimental results verify the effectiveness of the designed system.

A Novel Design of High Resolution MEMS Gyroscope Using Mode-Localization in Weakly Coupled Resonators

This paper presents a novel design for a high resolution microelectromechanical systems (MEMS) technology based resonant gyroscope using the mode-localization effect in weekly coupled resonators (WCRs) as a mechanism for sensing the input angular rate. The design consists of a single proof mass with two three degree-of-freedom (3-DoF) WCRs systems attached on either side. The MEMS gyroscope is designed according to the microfabrication constraints of the foundry process, silicon-on-insulator multi-user MEMS process (SOIMUMPs). The shift in the resonance frequency values, amplitude ratios of the WCRs, and amplitude ratios difference of two sets due to electrostatic stiffness perturbation, corresponding to the input angular rotation, are discussed as an output metric for the measurement of angular rate. The results show that the amplitude ratio difference as an output metric allows to achieve a linear output response and large dynamic range in comparison to the shift in the amplitude ratio and resonance frequency in 3-DoF WCRs in a single set. The dynamic range and resolution of the MEMS gyroscope in terms of maximum allowed resonators amplitude and noise floor is discussed. The proposed MEMS gyroscope design has a sensitivity of 62830 ppm/°/s based on a difference in the amplitude ratios of resonators in two 3-DoF WCRs systems and a dynamic range of ±100 °/s. The resolution of the MEMS gyroscope is 31.09 × 10-6 °/s which is significantly higher than existing MEMS gyroscopes and is comparable to traditional bulky ring laser gyroscopes. This high resolution makes the proposed MEMS gyroscope design suitable for use in applications such as earth rotation rate measurement for gyrocompassing and high precision robotics.

High-precision location for occluded reference hole based on robust extraction algorithm

The reference hole is significant for pre-positioning in high-precision robot drilling. The visual and optical measurement of such holes is of great benefit in terms of improving location accuracy during robot drilling and subsequent rivet-in-hole assembly. However, the detection and location of the reference hole via visual sensors still presents signifcant challenges, owing to the occlusion of perforator clips prior to practical drilling. This study proposes a robust extraction algorithm, based on gray clustering and edge detection, for locating the occluded reference holes (ORH). Firstly, the boundary box of the ORH is segmented using a template matching and density clustering algorithm. Secondly, the discrete arcs of the ORH are extracted via a combination of K-means clustering, pixel-intensity, and concave points extraction based on edge concavity. Finally, the target arcs are filtered and obtained based on their ellipse geometric properties, followed by the center extraction of the ellipse fitting. The experimental results show that the location accuracy achieved in this way is within 0.03 mm, which is sufficiently accurate for robot drilling. Moreover, the ORH data can be extracted and located successfully even in challenging industrial environments, with varying levels of illumination.

Automatic high-precision measurement technology of special-shaped surface parts based on robot arms

In order to meet the requirements of large-scale, special-shaped surface, high-precision surface measurement of product parts, an automated, high-precision robot arm measurement system based on industrial robots is proposed. According to the D-H method, the relative posture conversion relationship between the robot arm and the elastic probe is discussed. In addition, on the premise of considering the contact deformation between the elastic probe and the measuring surface, the coordinate data of the measuring point is obtained based on the probe deformation model. At the same time, the accuracy calibration is performed by means of visual photogrammetry, and the validity of the coordinate measurement data of the profiled surface is guaranteed.

Multibody Dynamics of Nonsymmetric Planar 3PRR Parallel Manipulator with Fully Flexible Links

This paper presents the implementation of the floating frame of reference formulation to model the flexible multibody dynamics of a nonsymmetric planar 3PRR parallel manipulator. All of the links, including the moving platform, of the manipulator under study are assumed flexible whereas the joints are assumed rigid. Using the Euler-Bernoulli beam, the flexibility of the links is modeled by using the Rayleigh-Ritz and finite element approximations. In both approximations, fixed-free boundary conditions are applied to the elastic coordinates of the links. These boundary conditions enable the evaluation of the elastic displacement at a link tip coincident with the end-effector of the manipulator which is of interest in the high precision robotics application. Both the approximations were compared by applying two different types of loads to the manipulator. It is shown that the elastic displacements obtained by using both the approximations have an agreement with a slight difference in the magnitude. In addition, the sensitivity analysis shows that the rigidity of the manipulator is much affected by the in-plane depth of the manipulator links’ cross section.

Research and Development of High Precision Robot Automatic Docking System Based on mxAutomation

In this paper we designs an automatic docking system to simulate the precision docking of the key components in aerospace assembly line. By using the robot to make the actual measurement of the experimental workpiece, we figure out the spatial coordinate system of the workpiece which correspond to the robot world coordinate system. This coordinate system is used to automatically control the robot to calculate the motion trajectory and complete the precision docking work. This system is characterized by the use of Siemens PLC to control the KUKA robot dynamically through the KUKA-TIA-Library interface, which can meet the requirements of flexibility and customization in aerospace industry.

An articulated finger driven by single-mode piezoelectric actuator for compact and high-precision robot hand.

In this paper, a novel finger driven by single-mode piezoelectric actuator for a compact and high-precision robot hand is proposed. Three piezoelectric actuators are articulated by two sets of connecting elements to form the finger. The finger utilizes a single model of the piezoelectric actuator to generate friction force to drive the joint. Without the difficulty to adjust for the coincidence of modal frequencies, the design of the piezoelectric actuator has fewer restrictions on size and structure; thus, the finger has a compact structure. The bidirectional motion of the joint is achieved by changing the temporal phase difference of two excitation signals applied on the two adjacent piezoelectric actuators. In addition, due to the characteristics of piezoelectric drive, such as power cut self-locking and quick response, the finger has a high resolution to realize micromanipulation for high precise movement. In our design, the first order longitudinal vibration mode of the piezoelectric actuator is used to generate the friction force. By using a finite element model, the geometric parameters of the piezoelectric actuator are obtained. A prototype of the finger is fabricated and experimentally investigated, the size (111 × 10 × 10 mm) is approximately 1.5 times that of a human middle finger, and the weight is 0.11 kg. The experimental results indicate that the angular speed of the prototype reaches 6.6 rad/s, the resolution is 20 mrad, and the startup and shutdown response times are 26 ms and 7 ms under a voltage of 400 Vpp, respectively. The fingertip force is 0.27 N under a voltage of 400 Vpp. The proposed finger has a compact size and simple structure with a high resolution (20 mrad).

Adaptive Iterative Learning Control of Robot Manipulators for Friction Compensation

Iterative learning control (ILC) has been well recognized for its ability to improve the tracking performance of systems that perform repetitive tasks. Its achievable performance, however, can be significantly degraded by the presence of non-repetitive disturbances which vary every iteration. Such may be a case for high-precision robot manipulators which are commonly subject to nonlinear and velocity-dependent friction forces. With a traditional PD-type ILC scheme, as joint velocities change along iterations, friction forces can vary substantially and deteriorate the performance of ILC. To address this problem, we propose an adaptive ILC algorithm, in which an adaptive friction compensation signal is introduced with ILC to adaptively identify the friction model over multiple iterations. Theoretical convergence analysis is provided with simulation verification on a 3-degree-of-freedom (DOF) planar manipulator. Experimental verification is also performed on a 5-DOF robot for silicon wafer handling. The verification results show that the proposed adaptive ILC approach can achieve significantly better tracking performance than traditional ILC methods.

Ultrasensitive Flexible Proximity Sensor Based on Organic Crystal for Location Detection.

A new type of flexible proximity sensor that uses a microsized organic crystal as the sensing element is demonstrated. The two-terminal organic sensor can accurately perceive the external objects, such as the human finger, fiber, and even atomic force microscopy tip. The proximity sensor shows an unprecedented distance resolution of 0.05 mm, which is 2 orders of magnitude higher than that of the previously reported conventional capacitor proximity sensors. A novel method has been proposed to realize the location detection of the approaching unknown-charge object by changing the distance between the stimulus and the sensor. Our results open a new route to realize an ultrasensitive perception of objects, making it a promising candidate for applications in artificial intelligence, healthcare systems, and high-precision robots.

High precision intelligent flexible grasping front-end with CMOS interface for robots application

This paper presents a high-precision intelligent flexible robot grasping front-end with an integrated capacitive tactile sensor array and a conditioning chip. The capacitive tactile sensor is the primary part of the front-end, it determines the overall performance. The micro-needle array sandwich structure in the tactile sensor increases the repeatability and stability, and ensures the sensitivity. The assembled sensor exhibits a saturation at 10.53 N (421 kPa) with a sensitivity of 1.9%/kPa. Furthermore, a conditioning chip is utilized in a custom readout interface to achieve better performance by reducing signal attenuation, and to increase the compatibility of the front-end. The chip is optimized for the parasitic shunt capacitance in the capacitor array. A dual bidirectional charge-discharge conversion method and a two-port detection method are matched to achieve the goal of reducing the shunting influence, and attenuating the offset voltage or the noise input effects. A prototype of the interface has been fabricated using 180-nm CMOS technology. Sensor with the value of 0.5 pF shunted by capacitors of 47 pF has been detected with an error of 1% within 100 us.

Human Joint Angle Estimation with Inertial Sensors and Validation with A Robot Arm.

Traditionally, human movement has been captured primarily by motion capture systems. These systems are costly, require fixed cameras in a controlled environment, and suffer from occlusion. Recently, the availability of low-cost wearable inertial sensors containing accelerometers, gyroscopes, and magnetometers have provided an alternative means to overcome the limitations of motion capture systems. Wearable inertial sensors can be used anywhere, cannot be occluded, and are low cost. Several groups have described algorithms for tracking human joint angles. We previously described a novel approach based on a kinematic arm model and the Unscented Kalman Filter (UKF). Our proposed method used a minimal sensor configuration with one sensor on each segment. This paper reports significant improvements in both the algorithm and the assessment. The new model incorporates gyroscope and accelerometer random drift models, imposes physical constraints on the range of motion for each joint, and uses zero-velocity updates to mitigate the effect of sensor drift. A high-precision industrial robot arm precisely quantifies the performance of the tracker during slow, normal, and fast movements over continuous 15-min recording durations. The agreement between the estimated angles from our algorithm and the high-precision robot arm reference was excellent. On average, the tracker attained an RMS angle error of about 3(°) for all six angles. The UKF performed slightly better than the more common Extended Kalman Filter.

Analysis of a novel high-precision 5-degrees of freedom magnetic resonance imaging-compatible surgery robot for needle-insertion prostate brachytherapy

In this paper, we focus on the design requirement of a high-precision magnetic resonance imaging-compatible robot for prostate needle-insertion surgery, which is actuated by five ultrasonic motors to achieve the goal of needle posture adjustment and prostate puncture. After a brief introduction to the robot, the direct and inverse kinematic equations are deduced. In order to show the relationship of the velocity between the actuators and the end effector, the Jacobian matrix is derived by formulating a velocity closed-loop equation for each limb. The kinematics is carried out by minimizing a global and comprehensive dimensional synthesis conditioning index subject to transmission angle and range of motion of the mechanism constraints. The dimensional parameters are obtained for achieving a good kinematic performance throughout the entire task workspace by an example, and finally the reachable workspace of the robot is calculated.

Extension Adaptive Control of a High-Speed and High-Precision Three-Axis Parallel Robot

In the paper a high-speed and high-precision three-axis parallel robot was studied as the research object and a kind of extension controller used for the control system was established. Seeing properties that the adaptive controller is good at dealing with the same and slowly time-varying problem and extension controller is good at dealing with time-varying and mutation problem. The advantages of the two kinds of controllers were combined and a new type of extension adaptive controller was developed. The simulation results show that the extension adaptive controller can greatly improve end implementation tracking precision of the parallel robot and satisfy the robot control requirements. The methods have broad prospect in application of the parallel robot control.