Applications Of Parallel Robots Research Articles

Deep learning-based predicting and compensating method for the pose deviations of parallel robots

The static pose accuracy is regarded as a crucial performance indicator for parallel robots, which is inevitably affected by the geometric and nongeometric errors. However, an accurate error model for parallel robots is highly complex, especially for mathematical modeling and identifying non-geometric errors. This limitation hampers the application of parallel robots in high-precision processing and manufacturing fields. To enhance the performance of parallel robots and address the complexities in establishing their error models, a deep learning-based predicting and compensating method is investigated, which can accurately predict their pose deviations. This method ingeniously integrates the spatial feature extraction capabilities of convolutional neural networks, the bidirectional dependency capturing prowess of bilateral long short-term memory networks, and the feature significance discernment offered by squeeze-and-excitation networks. Subsequently, the pose deviations are definitely predicted by this method and are pre-compensated into nominal pose so as to improve the performance. A pose-deviation pairs dataset is established to accomplish the comparison of the investigated method with the two commonly used artificial neural network and long short-term memory on the 6-UPS parallel robot. Experiment on the 6-UPS parallel robot against traditional kinematic calibration methods demonstrate the investigated method achieves satisfactory pose accuracies, with the ability to reduce pose deviations by 88.60 %. Meanwhile, the effectiveness and general applicability of this method have also been validated by successful implementation on a 6-UCU parallel robot.

Multi-objective genetic algorithm and Castigliano’s theorem for stiffness optimisation of parallel robots: case study of conventional Stewart platforms

ABSTRACT Study of stiffness characteristics plays a key role in application of parallel robots in precision manufacturing. In this study, stiffness index improvement is utilised as the objective function to obtain optimal configurations and dimensions for parallel robots. The optimisation goal is to maximise the stiffness index throughout workspace of the robots. First, stiffness of the robots is obtained by the strain energy of main components of the robots and Castigliano’s theorem. For a more realistic simulation, compliance of moving platform of the robots is considered. Then a non-dominated sorting genetic algorithm (NSGA-II) is utilised to solve the optimisation problem. A comprehensive case study of stiffness analysis of three conventional SPS (spherical– prismatic–spherical) Stewart platforms to examine such a platform’s optimised design is performed. The relationship between the objective and decision spaces is investigated. A similar approach can be utilised to study optimised design for other parallel robots. Findings of this study provide a general stepwise and conceptual approach to the stiffness analysis of parallel robots that depends on design parameters and configuration of the robots. In case of Stewart platforms, 3SPS configuration was found to be optimised in terms of stiffness performance in their workspace.

Kinematic Calibration of Parallel Robots Based on L-Infinity Parameter Estimation

Pose accuracy is one of the most important problems in the application of parallel robots. In order to adhere to strict pose error bounds, a new kinematic calibration method is proposed, which includes a new pose error model with 60 error parameters and a different kinematic parameter error identification algorithm based on L-infinity parameter estimation. Parameter errors are identified by using linear programming to minimize the maximum difference between predictions and workspace measurements. Simulation results show that the proposed kinematic calibration has better kinematic parameter error estimation and fewer pose errors when measurement noise is less than kinematic parameter errors. Experimental results show that maximum position and orientation errors, respectively, based on the proposed method are decreased by 86.48% and 87.85% of the original values and by 14.32% and 18.23% of those based on the conventional least squares method. The feasibility and validity of the proposed kinematic calibration are verified by improved pose accuracy of the parallel robot.

Analysis of Position, Pose and Force Decoupling Characteristics of a 4-UPS/1-RPS Parallel Grinding Robot

For the application of parallel robots in the grinding industry, a parallel robot equipped with a constant force actuator that produces a constant force for grinding is designed. To study the characteristics of the parallel robot’s spatial positions and poses, the inverse solutions of the moving platform’s spatial positions and poses as well as the workspace where objects were ground were established by using DH parameters and geometric methods. The experimental results showed that the workspace where objects were ground was a cylinder with a cross section similar to a symmetric circular sector. To analyze the characteristics of the forces produced by the parallel robotic system, the dynamics equation was established via the Newton–Euler method to verify the rationality of the force decoupling design. Theoretical calculation combined with simulation and experimental analyses confirmed the viability of the theoretical analyses which lay a theoretical foundation for the design, manufacture and control of the parallel robotic system proposed in this paper.

Kinematic calibration of a 5-axis parallel machining robot based on dimensionless error mapping matrix

Accuracy problem is one of the most challenging issues for the application of parallel robots in manufacturing industry, and kinematic calibration is a feasible approach to solve it. Although lots of researches have brought up a diversity of calibration methods, there are still rooms for the improvement of the accuracy, efficiency and robustness of these calibration effects. In this paper, an improved method for kinematic calibration of a 5-axis parallel machining robot is proposed, which includes a new forward kinematic solution (FKS) based on dual quaternion and a modified error modeling process leading to dimensionless error mapping matrixes (EMMs). On this basis, an iterative identification procedure is schemed, and the kinematics and identification simulations are carried out. The kinematics simulation results show that the proposed FKS has wider convergence range and faster computation speed than Levenberg-Marquardt algorithm, while the identification simulation results show that the residual pose errors with the proposed dimensionless EMMs are lower than that with the conventional EMM in various units. Additionally, the procedure of the full pose measurement with a laser tracker and an auxiliary tool is introduced, and thereby the contrast experiments of kinematic calibration on the prototype are conducted. The experiment results indicate that the residual position and orientation errors based on the dimensionless EMM decrease by 97.67% and 86.85% of the original values, respectively, at least, and by 76.77% and 38.65% of that based on the conventional EMM, respectively, at most. Consequently, it is further confirmed that the proposed calibration method is effective in enhancing the identification accuracy of the geometric errors and improving the positioning accuracy of the studied parallel robot.

Kinematic Characteristics and Applications of Parallel Robots

Kinematic Characteristics and Applications of Parallel Robots

Computationally Efficient Inverse Dynamics of a Class of Six-DOF Parallel Robots: Dual Quaternion Approach

Computationally efficient inverse dynamics is crucial to the real-time application of parallel robots. This paper provides a computationally more efficient solution to the inverse dynamics of a class of six-DOF parallel robots based on the dual quaternion approach under the principle of virtual power. A unit dual quaternion is selected as the generalized coordinates of the system. The equations of motion are then constructed by the principle of virtual power. The dual quaternion constraints are eliminated by the null space formulation to obtain the inverse dynamic solution. It is revealed that in the new solution, the Jacobian matrices and the orthogonal complement matrix are all linear with respect to the generalized coordinates. Additionally, the positions, velocities and accelerations of all bodies are quadratic with respect to the generalized coordinates, velocities and accelerations. Such succinct expressions render the new solution computationally more efficient. The execution time of the dual quaternion approach and the traditional one are compared under the same condition by two different six-DOF parallel robots: 6-UPS and 6-PUS. The results show that the new solution can save the computational cost by 43.45% and 38.45% respectively for the two robots, illustrating the effectiveness of the proposed approach.

Translational shaking tests achieved on a 6-DOF hydraulic parallel manipulator

Purpose – The paper aims to achieve translational shaking tests on a 6-DOF hydraulic parallel manipulator. Shaking tests are commonly performed on shaking tables, which are generally used for small motion ranges and are usually financially costly. The research is required to generate shaking motions in three translational directions for a specimen for shaking tests, but it also needs to produce 6-degree of freedom (DOF) motions with large motion ranges. Design/methodology/approach – A hydraulic 6-DOF (degree of freedom) parallel manipulator is applied to achieve this goal. The link-space control is adopted for the manipulator, and PID controller and feed-forward controller are used for each loop of the system. A hybrid reference signal generator is proposed by using a shaking controller, which is developed to convert the shaking motion into position signal. The converted result is directly added to the pose signal. The whole real-time control system is realized by using MATLAB xPC Target. Findings – The developed method is verified on the hydraulic 6-DOF parallel manipulator with specimen. Experiments show very promising results that the proposed technology is really applicable to perform translational shaking tests on the hydraulic parallel manipulator. Originality/value – A simple yet efficient solution is proposed that allows shaking tests in three translational directions performed on the hydraulic 6-DOF parallel manipulator with wide motion ranges. The paper presents a state-of-the-art related to the applications of parallel robots in several fields of technology.

Kinematic calibration of a parallel robot using coordinate measuring machine

In the applications of parallel robots, kinematic calibration is required to eliminate the errors resulting from the manufacturing and assembly. In this paper, a new method for calibrating a parallel robot is proposed. An error model for kinematic calibration is constructed using differential geometry method. All leg length information and pose error are obtained based on measurement results coordinate measuring machine. A nonlinear least squares procedure is employed to determine the kinematic parameters. The parameters of the measurement error in the leg sensors are considered during kinematic modeling and parameter identification program. Experimental results presented demonstrate that the root mean square pose error can be improved at 80% with the 48 identified parameters. Key words: Parallel robot, error modeling, kinematic calibration, parameter identification, nonlinear least squares.

Field and service applications - Exploring deep sea by teleoperated robot - An Underwater Parallel Robot with High Navigation Capabilities

This article presents a new application of parallel robots as underwater vehicles. The article shows the methodology applied in the design process, its modeling and the building of a novel underwater parallel robot (UPR). The designed robot is based on the well-known Stewart-Gough (S-G) platform that leads us to a new concept of geometry-variable underwater robot. The main advantage of this study is that the S-G platform allows not only a relative orientation between the two rings, but also a relative displacement, which increases the navigation capabilities of other gimbaled thruster designs. Navigation and control of this new type of underwater robots lead to new challenges that still have to be solved.

PREDICTIVE CONTROL APPLIED TO PLANAR PARALLEL ROBOTS

The design of suitable control is essential part of application of parallel robots. Together with appropriate control, the parallel robots are promising way to significantly improve accuracy and speed of machine tools in industrial production. This paper deals with the design and results of one possible control approach represented by model-based predictive control in absolute formulation. It explains exact linearization of used, initially nonlinear models, which are sequentially transformed to discrete state-space form. Control algorithm is derived in square-root form. The results are substantiated by real laboratory experiments showed in several representative figures.