Kinematic Performance Research Articles

STUDY ON THE PIECEWISE CONSTANT CURVATURE KINEMATIC MODEL OF A TWO-SEGMENT ROBOT

This study presents the Piecewise Constant Curvature (PCC) kinematic model of a two-segment continuum robot, offering a clear and illustrative approach to deriving the kinematics of a soft manipulator. Analytical expressions are developed to relate the endpoint positions of the robot’s pneumatic arm segments to the lengths of its pneumatic muscles. The kinematic model has two contrasting features: it is general enough to be applicable for various continuum robot arms, yet it does not account for specific structural details, requiring adaptation for different soft robot designs. The step-by-step methodology, visual clarity, and extension of the PCC model to a two-segment robot distinguish this research from existing studies. This approach can be extended to multi-segment soft manipulators, offering a valuable framework for further exploration in the field.

Research on the Entrance Damage of Carbon Fiber-Reinforced Polymer/Ti6Al4V Stacks in Six-Degrees-of-Freedom Robot Drilling

Carbon fiber-reinforced polymer (CFRP)/titanium alloy (Ti6Al4V) stacks are widely used in the aerospace industry due to their excellent physical properties. The substantial demand for drilling components in the aerospace industry necessitates the implementation of enhanced processing efficiency and drilling quality standards. Six-degrees-of-freedom robots are commonly used in the aerospace industry due to their high production efficiency, high flexibility, and low labor costs. However, due to the weak stiffness, chatter is prone to occur during processing, which has a detrimental impact on the quality of the finished product. As an advanced processing technology, ultrasonic-assisted machining technology can effectively reduce the cutting force and suppress the chatter in the drilling process, so it is widely used in production. In this paper, first, the robot kinematic (dexterity) and stiffness performance is analyzed. Then, the appropriate range of the machining plane and the posture of the robot in the workspace are selected. Finally, the vibration and CFRP entrance damage during the machining process are compared and studied in conventional robotic drilling (CRD) and ultrasonic-assisted robotic drilling (UARD). The experimental results demonstrate that the UARD is an effective method for reducing vibration during the machining process. Compared with the CRD, the CFRP entrance delamination damage in UARD is reduced. Under the appropriate processing parameters, the entrance delamination factor could be reduced by 15%, and the burr height could be reduced by 45%. Obviously, the UARD is a promising process to improve the CFRP entrance delamination damage.

Manipulator Differential Kinematics: Part I: Kinematics, Velocity, and Applications [Tutorial

Manipulator kinematics is concerned with the motion of each link within a manipulator without considering mass or force. In this article, which is the first in a two-part tutorial, we provide an introduction to modelling manipulator kinematics using the elementary transform sequence (ETS). Then we formulate the first-order differential kinematics, which leads to the manipulator Jacobian, which is the basis for velocity control and inverse kinematics. We describe essential classical techniques which rely on the manipulator Jacobian before exhibiting some contemporary applications. Part II of this tutorial provides a formulation of second and higher-order differential kinematics, introduces the manipulator Hessian, and illustrates advanced techniques, some of which improve the performance of techniques demonstrated in Part I. We have provided Jupyter Notebooks to accompany each section within this tutorial. The Notebooks are written in Python code and use the Robotics Toolbox for Python, and the Swift Simulator to provide examples and implementations of algorithms. While not absolutely essential, for the most engaging and informative experience, we recommend working through the Jupyter Notebooks while reading this article. The Notebooks and setup instructions can be accessed at https://github.com/jhavl/dkt.

Convex geometric motion planning of multi-body systems on lie groups via variational integrators and sparse moment relaxation

This paper reports a novel result: with proper robot models based on geometric mechanics, one can formulate the kinodynamic motion planning problems for rigid body systems as exact polynomial optimization problems. Due to the nonlinear rigid body dynamics, the motion planning problem for rigid body systems is nonconvex. Existing global optimization-based methods do not parameterize 3D rigid body motion efficiently; thus, they do not scale well to long-horizon planning problems. We use Lie groups as the configuration space and apply the variational integrator to formulate the forced rigid body dynamics as quadratic polynomials. Then, we leverage Lasserre’s hierarchy of moment relaxation to obtain the globally optimal solution via semidefinite programming. By leveraging the sparsity of the motion planning problem, the proposed algorithm has linear complexity with respect to the planning horizon. This paper demonstrates that the proposed method can provide globally optimal solutions or certificates of infeasibility at the second-order relaxation for 3D drone landing using full dynamics and inverse kinematics for serial manipulators. Moreover, we extend the algorithms to multi-body systems via the constrained variational integrators. The testing cases on cart-pole and drone with cable-suspended load suggest that the proposed algorithms can provide rank-one optimal solutions or nontrivial initial guesses. Finally, we propose strategies to speed up the computation, including an alternative formulation using quaternion, which provides empirically tight relaxations for the drone landing problem at the first-order relaxation.

A digital design framework for the dimensional optimization of parallel robots based on kinematic and elasto-dynamic performance

The dimensional optimization based on kinematic and dynamic performance indices is proven significant for improving the operational performance of parallel robots. As the pose-dependent performances vary with the dimensional parameters, there are still many challenges in the optimal design of parallel robots, such as the possible conflict amongst different performance indices and computational expensiveness. By considering a 4-DOF high-speed parallel robot as an illustrative example, this paper presents a framework for the optimal design of parallel robots by integrating skeleton modeling, CAD-CAE integration and multi-objective optimization techniques. In this approach, the models for kinematic and elasto-dynamic performance evaluation are first developed using the CAD and CAE techniques, respectively. After evaluating the performance distributions over the task workspace, several reference poses representative of multiple neighboring sample poses are determined to formulate corresponding local performance indices by using the Hard C-Means (HCM) clustering analysis algorithm. This consideration leads to the determination of the optimal dimensions by investigating the Pareto-optimal solutions of a multi-objective optimization problem, allowing the conflict amongst different performance indices to be appropriately handled and the computational time to be saved significantly. The results of the case study show that the proposed approach can significantly enhance the elastic dynamic performance while ensuring that the kinematic performance is not excessively compromised, when compared to the performance of existing physical prototype of the robot. A software package has been developed using the proposed framework, providing a highly accessible way for designing various types of parallel/hybrid robots based on CAD and CAE techniques.

MpcMech: Multi-Point Conjugation Mechanisms

A mechanism is an assembly of moving parts interconnected by joints to transfer an input motion to a desired output motion. Traditionally, to generate a complex motion, mechanisms are modeled by selecting and combining a number of mechanical parts with simple shapes such as links, gears, and cams. Combining multiple mechanical parts results in a mechanism with an intricate topology, which not only complicates assembly and maintenance but also deteriorates the functionality of generating motions due to accumulation of manufacturing imprecisions. To get rid of these limitations, we study mechanisms with a single pair of moving parts for generating complex motions. We model the pair of moving parts as a pair of conjugate surfaces with multiple conjugation points, forming a multi-point conjugation mechanism. To study this new mechanism, we establish a connection between conjugate surface pairs and form-closure grasps to formulate a dynamic form closure condition under which one conjugate surface is able to continuously transfer the motion to the other conjugate surface by utilizing multiple conjugation points. Guided by the condition, we propose an optimization-based approach to model the geometry of a multi-point conjugation mechanism for exactly generating a user-specified motion, in 1-, 2-, or 3-DOF motion space. The core of our approach is to model multiple conjugate curve pairs that satisfy various requirements in multi-point conjugation, dynamic form closure, and surface fabricability. We demonstrate the effectiveness of our approach by modeling different classes of multi-point conjugation mechanisms to generate various motions, evaluating the mechanisms' kinematic performance with 3D printed prototypes, and presenting three applications of these mechanisms.

Full Forward Kinematics of Lower-Mobility Planar Parallel Continuum Robots

In rigid lower-mobility parallel manipulators the motion of the end-effector is partially constrained due to a combination of passive kinematic pairs and rigid components. Translational mechanisms, such as the Delta manipulator, are the most common ones among this type of mechanisms. When flexible elements are introduced, as in Parallel Continuum Manipulators, the constraint is no longer rigid, and new challenges arise in performing certain motions depending on the degree of compliance. Mobility analysis shifts from being purely a geometric issue to one that heavily relies on force distribution within the mechanism. Simply converting classical lower-mobility rigid parallel mechanisms into Parallel Continuum Mechanisms may yield unexpected outcomes. This work, making use of a planar parallel continuum Delta manipulator, on the one hand, presents two different approaches to solve the Forward Kinematics of planar continuum manipulators, and, on the other hand, explores some challenges and issues in assessing the resultant workspace for different design alternatives of this kind of flexible manipulators.

Light‐Manipulated Millimeter‐Scale Swimming Robot for Precise Navigation

AbstractMicro‐swimming robots have been increasingly emphasized in the fields of targeted drug delivery and water surface cleaning, which mainly use open external structures or external environments to assist navigation, but there are still salient problems, such as the difficulty of stable capture and poor navigation accuracy. Theoretically, a light‐driven swimming robot can have a symmetrical embedded structure to constrain surface tension gradient forces and thermophoretic forces in a wide range of directions and convert them into precise directional forces. Therefore, a sustained‐capture swimming robot is developed with precise navigation consisting of TiO2/polypyrrole (PPy) composites containing a symmetric inner truncated‐cone hole structure and realized multiple controllable motion patterns. Excitingly, the capture motion of the TiO2/PPy inner truncated‐cone hole structure robot “TPHR” can be accurately controlled by programmable automation, with capture travel speeds of up to ≈23.64 mm s−1. Its excellent kinematic performance stems from the high photothermal conversion efficiency (≈47.83%) of the composite and the synergistic effect between thermo‐capillary and thermo‐convective flows. Furthermore, a patterning precision movement, water surface oil‐cleaning microstructure assembly, etc. are realized, reflecting the engineering application value of TPHR. This structure provides a novel strategy for the development of micro‐swimming robots with stable capture and sustainable motion.

Synthesis and Analysis of 3-CPC Space Mobile Parallel Mechanism

Abstract The degree of freedom of 3-CPC space mobile parallel mechanism is calculated according to the screw theory, and the kinematics model of 3-CPC space mobile parallel mechanism is established by coordinate transformation method. By analyzing the forward and inverse kinematics, the Jacobian matrix 3-CPC space mobile parallel mechanism is derived. The workspace is obtained, and the kinematics performance is simulated. The results show that the forward and inverse kinematics of 3-CPC space mobile parallel mechanism is simple to solve, the workspace is large, and the mechanism has good kinematics performance and strong practical value. Finally, the 3-CPC space mobile mechanism is applied to the vibrating screen for material screening, and the motion trajectory of the moving platform is obtained. The kinematic performance analysis 3-CPC space mobile parallel mechanism provides the theoretical basis for the application of the mechanism.

Tensor based approach for tooth contact analysis of planar and spatial gearing contact

This paper presents a new method for analysing gear tooth contact, leveraging tensor notation and discrete differential geometry. Existing analytical and numerical methods often face challenges in convergence and computational efficiency. Our proposed approach involves defining a novel tensor notation and applying it to the gear tooth contact kinematics problem. By discretizing the tooth surfaces and using tensor operations, we can accurately determine the kinematics, path of contact, and transmission error of the gear pair. To validate our approach, we compared its results with those obtained from commercial software, KISSsoft and KiMOS. The results demonstrated high accuracy, with mean absolute errors below 0.08 for specific sliding, 0.003 for sliding factor, and 0.1μm for transmission error. Furthermore, we applied our method to analyse non-involute gear types, such as S-gears, pin gearing and cosine gears. Our findings revealed the kinematic performance and contact characteristics of these gear types, providing valuable insights for gear design and optimization. In conclusion, the proposed tensor-based approach offers a promising alternative for gear tooth contact analysis, providing accurate and efficient results for a wide range of gear types.

АВТОМАТИЗОВАНА СИСТЕМА УПРАВЛІННЯ МАНІПУЛЯЦІЙНИМИ РОБОТАМИ

The article deals with the development of an automated control system for manipulative robots based on a mathematical model and the use of an Android mobile device for remote control. The main goal of the study is to create a prototype of a robotic arm that can be controlled using wireless technology, which provides convenience and efficiency in real-time control. The 4-degree-of-freedom robotic arm was created and is controlled through a mobile application developed using MIT App Inventor, which is based on Bluetooth technology. Data from the application is transmitted serially via a Bluetooth transmitter, processed by the receiver and used to control the robot's movements. The development and implementation of such a control system is an important step in the development of robotic technologies, as it not only provides a high level of automation but also allows robots to be used in various fields of activity, such as industry, medicine, logistics and other areas where the accuracy and speed of task performance are critical. A systematic approach to real-time control of manipulation mechanisms allows for high precision in control, which is especially important in a dynamically changing working environment. One of the key features of this system is the use of mathematical models that allow for a detailed analysis of the manipulator's kinematics and dynamics. This makes it possible to optimally control the robot's movements, which increases its flexibility in interacting with the environment. Mathematical models provide the ability to predict and correct robot actions in real time, which minimises the risk of errors and increases the overall efficiency of the system. One of the main advantages of using an Android mobile application is its accessibility and ease of use. Modern mobile devices have considerable computing power, which makes it possible to integrate complex control algorithms into the application and control robotic systems without the need for expensive specialised equipment. The application, created using MIT App Inventor, allows the user to easily configure robot control parameters, receive real-time feedback and control all aspects of the robot through a user-friendly interface. Bluetooth data transmission is another important component of the system, as it provides reliable and fast communication between the mobile device and the robot. The data is transmitted sequentially, which allows for precise coordination of the robot's movements in accordance with the commands coming from the app. This approach also minimises delays in the transmission of commands, which is key for real-time tasks. During the experiments, successful tests of the linear movement of the robotic arm were conducted, which confirmed the system's performance and its potential for further development. The tests demonstrated that the robot is able to accurately perform tasks related to linear movement, which is the basis for its use in more complex scenarios. This opens up wide opportunities for the introduction of such robots in various fields where it is necessary to perform tasks with high accuracy and speed. In general, the proposed system combines advanced technologies such as mathematical modelling, wireless communication and mobile applications, which ensures high flexibility and efficiency in the management of robotic systems. The use of mathematical models allows not only for precise control of the robot's movements, but also for adaptation to changes in the environment, which makes the system more stable and reliable in use.

Home-based guidance training system with interactive visual feedback using kinect on stroke survivors with moderate to severe motor impairment

The home-based training approach benefits stroke survivors by providing them with an increased amount of training time and greater feasibility in terms of their training schedule, particularly for those with severe motor impairment. Computer-guided training systems provide visual feedback with correct movement patterns during home-based training. This study aimed to investigate the improvement in motor performance among stroke survivors with moderate to severe motor impairment after 800 min of training using a home-based guidance training system with interactive visual feedback. Twelve patients with moderate to severe stroke underwent home-based training, totaling 800 min (20–40 min per session, with a frequency of 3 sessions per week). The home-based guidance training system uses Kinect to reconstruct the 3D human body skeletal model and provides real-time motor feedback during training. The training exercises consisted of six core exercises and eleven optional exercises, including joint exercises, balance control, and coordination. Pre-training and post-training assessments were conducted using the Fugl-Meyer Assessment-Upper Limb (FMA-UE), Fugl-Meyer Assessment-Lower Limb (FMA-LE), Functional Ambulation Categories (FAC), Berg Balance Scale (BBS), Barthel Index (BI), Modified Ashworth Scale (MAS), as well as kinematic data of joint angles and center of mass (COM). The results indicated that motor training led to the attainment of the upper limit of functional range of motion (FROM) in hip abduction, shoulder flexion, and shoulder abduction. However, there was no improvement in the active range of motion (AROM) in the upper extremity (U/E) and lower extremity (L/E) joints, reaching the level of the older healthy population. Significant improvements were observed in both left/right and superior/inferior displacements, as well as body sway in the mediolateral axis of the COM, after 800 min of training. In conclusion, the home-based guidance system using Kinect aids in improving joint kinematics performance at the level of FROM and balance control, accompanied by increased mediolateral body sway of the COM for stroke survivors with moderate to severe stroke. Additionally, spasticity was reduced in both the upper and lower extremities after 800 min of home-based training.

A joint acceleration planning method for inverse kinematics of manipulator based on second-order system with variable impedance

The paper presents an angular acceleration planning method for joint space of manipulator to achieve real-time tracking tasks under joint constraint. To improve the performance of the algorithm and ensure the joint limit, the proposed method establishes a Second-order System with Variable Impedance (SSVI). The Second-order System is introduced in the joint space through the joint angular acceleration in second derivative of kinematics. The impedance parameters vary with different states of joint and the variable impedance produced virtual repulsive force to ensure that the joint motions are within the specified ranges when they are close to limits. The damping impedance contained in the system can improve convergence speed and suppress system oscillation and vibration caused by factors such as the visual noise. Simulation and experiment results verify that the method is effective and has faster convergence speed and more smooth motion compared with other methods.

Improved Bald Eagle Search Optimization Algorithm for the Inverse Kinematics of Robotic Manipulators.

The inverse kinematics of robotic manipulators involves determining an appropriate joint configuration to achieve a specified end-effector position. This problem is challenging because the inverse kinematics of manipulators are highly nonlinear and complexly coupled. To address this challenge, the bald eagle search optimization algorithm is introduced. This algorithm combines the advantages of evolutionary and swarm techniques, making it more effective at solving nonlinear problems and improving search efficiency. Due to the tendency of the algorithm to fall into local optima, the Lévy flight strategy is introduced to enhance its performance. This strategy adopts a heavy-tailed distribution to generate long-distance jumps, thereby preventing the algorithm from becoming trapped in local optima and enhancing its global search efficiency. The experiments first evaluated the accuracy and robustness of the proposed algorithm based on the inverse kinematics problem of manipulators, achieving a solution accuracy of up to 10-18 m. Subsequently, the proposed algorithm was compared with other algorithms using the CEC2017 test functions. The results showed that the improved algorithm significantly outperformed the original in accuracy, convergence speed, and stability. Specifically, it achieved over 70% improvement in both standard deviation and mean for several test functions, demonstrating the effectiveness of the Lévy flight strategy in enhancing global search capabilities. Furthermore, the practicality of the proposed algorithm was verified through two real engineering optimization problems.

Contributing factors to the improvement of conceptual understanding in a computer-based intervention in Newtonian dynamics

Students experience many difficulties learning the fundamental relationships in Newtonian mechanics, partly due to preexisting mental models that originate from their everyday lives. These preconceptions often persist even after instruction in mechanics and lead to a supposed incompatibility between physics lessons in school and personal experiences. This article presents research that focuses on students’ concept knowledge and conceptual understanding in the field of Newtonian dynamics. Interventions are presented that discuss authentic experiments with friction using different software as a tool. Overall, the interventions lead to an increase in conceptual understanding with a large effect size. A hierarchical linear model (HLM) is used to identify factors that lead to a larger or smaller increase in conceptual understanding of the topic. With the HLM, we infer that the pretest score, the students’ interest in how physical properties interrelate (interest in “theoretical physics”), prior physics performance (in kinematics in this case, measured in the physics grade), and the (intrinsic and extraneous) cognitive load influence the post-test score. We discuss possible explanations as to why these factors influence students’ conceptual change. Published by the American Physical Society 2024

Inverse Kinematics of Robotic Manipulators Based on Hybrid Differential Evolution and Jacobian Pseudoinverse Approach

Robot manipulators play a critical role in several industrial applications by providing high precision and accuracy. To perform these tasks, manipulator robots require the effective computation of inverse kinematics. Conventional methods to solve IK often encounter significant challenges, such as singularities, non-linear equations, and poor generalization across different robotic configurations. In this work, we propose a novel approach to solve the inverse kinematics (IK) problem in robotic manipulators using a metaheuristic algorithm enhanced with a Jacobian step. Our method overcomes those limitations by selectively applying the Jacobian step to the differential evolution (DE) algorithm. The effectiveness and versatility of the proposed approach are demonstrated through simulations and real-world experimentation on a 5 DOF KUKA robotic arm.

Propulsion and energy extraction performance of wave-powered mechanism considering wave and current

Wave-powered mechanism can extract wave energy as propulsion, enabling long-term ocean observation. The kinematic properties of wave propulsion mechanisms are susceptible to ocean current loads in addition to wave effects, presenting complex dynamic behaviors. In this paper, to understand the effects of ocean currents on the kinematic performances of wave propulsion mechanism, the dynamic performance of a wave propulsion mechanism in the combined condition of wave and current is analyzed based on numerical simulation method for fluid-rigid body coupling and experimental methods. The performance of the propulsion mechanism against the current under counter-current conditions and the contribution of flow to the propulsion performance under co-current conditions are discussed. The intrinsic relationship between wave height, current velocity and current direction is investigated, and the energy extraction performance of wave propulsion mechanism is analyzed. According to the results, the ability of propulsion mechanism to resist counter-current is obtained, and it is found that as the counter-current velocity increases, the hydrofoil will stall and the propulsion force and efficiency decreases significantly. Whilst, the co-current has a promoting effect on the forward of the mechanism, but within a certain range of co-current speed, the mechanism will be negatively affected by the shedding vortex. And the discrimination mechanisms for wave-dominated propulsion and current-dominated propulsion are obtained. This work reveals the combined effect of waves and currents on the motion performance of wave propulsion mechanism, providing a reference for the development of surface vehicles that utilize multiple ocean energies for synergistic propulsion.

Exploring artificial neural networks for the forward kinematics of a SCARA robotic manipulator using varied datasets and training optimizers

Abstract Although analytical methods are traditionally employed, the solution to the Forward Kinematics (FK) problem for Selective Compliance Assembly Robot Arm (SCARA) manipulator robots can prove intricate and computationally demanding. Recognizing this challenge, this study endeavors to introduce an intelligent approach by leveraging Artificial Neural Networks (ANNs) to address the FK problem specifically tailored for a four-degree-of-freedom (4-DoF) SCARA robot. To train the ANNs, we employ three distinct datasets, one with a fixed step size, one with a random step size, and one based on a sinusoidal signal. Moreover, the objective is to scrutinize the ANNs performance under the influence of three distinct training algorithms: Levenberg-Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). Through a systematic comparison of various ANN models, diverse training algorithms, and the three chosen datasets, the investigation reveals that optimal Mean Squared Error (MSE) results are achieved with random step size datasets for models with two hidden layers using the LM algorithm (MSE = 8.6099e-05). For the BR algorithm, the best MSE (8.0535e-05) was obtained with sinusoidal datasets and three hidden layers. For the SCG algorithm, the optimal MSE (1.1144e-04) was achieved with fixed step size datasets and one hidden layer. The accuracy of the ANN model is significantly influenced by the dataset, the choice of training optimizer, and the configuration of hidden layers. Consequently, further research could explore hybrid approaches that integrate evolutionary algorithms to leverage their respective strengths and improve overall ANN model performance.

Key performance indicators and reference values for turn performance in elite youth, junior and adult swimmers

ABSTRACT This study aimed to determine kinematic and kinetic key performance indicators (KPI) of swimming turn performance using principal component analysis (PCA) and multiple linear regression analysis and provide reference values using percentiles. Touch and tumble turn performances of male (n = 68) and female (n = 48) Swiss national team members from three age categories—adult (20.2 ± 2.7 yrs, 790 ± 57 points), junior (16.2 ± 0.8 yrs, 729 ± 53 points) and youth swimmers (14.4 ± 1.0 years of age, 667 ± 53 World Aquatics swimming points, respectively)—were assessed with a motion analysis system equipped with a force plate on the pool wall, one over- and four underwater cameras sampling forces at 500 Hz and footages at 100 Hz. The PCA reduced the 27 original variables by up to 15% depending on turn type and age category using Varimax component loading of >0.6 and explained up to 91% of the total variance. The highest Varimax component loadings for each principal component were used to determine KPI for each turn type and age category using multiple-regression analysis with total turn time as dependent variable. These KPI should be used to interpret turn performances and identify individual swimmers’ strengths, weaknesses and future potentials with the help of the percentiles as reference values.

Research on the inverse kinematics of heavy-load manipulator and end-effector for fusion reactor

The environment in Tokamak fusion reactor is hostile to remote handling (RH) equipment that maintains in-vessel components. Many maintenance tasks include transferring components, pipe cutting, and welding in the vacuum vessel (VV). To fulfill these maintenance works, a 7- degree-of-freedom (DOF) heavy load manipulator and a 3-DOF end-effector are designed and connected together to form a 10-DOF redundant robot. The inverse kinematics for such a high redundancy robot, considering obstacle avoidance in the complex space of VV, is a challenge. To solve this problem, the Jacobian method is adopted, and a method specially designed for obstacle avoidance of redundant robots working in the VV is integrated to simplify algorithm calculation and improve inverse solution efficiency. The algorithm is applied to solve the inverse kinematics of the redundant robot for the maintenance of the divertor plasma facing components (PFC) in VV. The results show that the inverse kinematics of the redundant robot can be solved quickly with high positioning accuracy. The method can also be used for other fusion reactor maintenance robots with some adjustments. The maintenance efficiency of redundant robot can be improved with the method which can be valuable for the whole remote handling process.