Inverse Kinematic Model Research Articles

Emotion-driven action interaction design in small quadruped robots: leveraging NXEIK multilevel network

This study introduces a facial expression-driven interaction method for small quadruped robots, featuring three layers: Perception (L1), Analysis (L2), and Expression (L3). L1 focuses on data acquisition and image stabilization, L2 on model training and emotion classification, and L3 on control feedback and interactive movements. The core NXEIK network model comprises the NAFNet for image stabilization, Mini-Xception for facial recognition, EANet for action mapping, and an inverse kinematics model. Validation on a self-designed robot platform demonstrated the method's ability to enhance jittery image data and outperform deep learning networks like ViT and ResNet-101 in facial expression classification. The NXEIK model enables the robot to adapt its movements to various expressions using only three parameter types. This research provides a feasible solution for enhancing human-robot interaction and movement design for flexible quadruped robots through facial expressions.

Model-Free Intelligent Control for Space Soft Robotic Manipulators

Given the advantages of softness, lightness, low cost, and interaction safety, inverse kinematic modeling and control of soft actuators has caused a research boom. However, in realizing dexterous manipulation of space large soft manipulators, it is much more difficult to achieve precise control not only because of the greater accumulation of errors in the multiple degrees of freedom and nonlinear properties of soft materials at large scales but also because of the inability of directly solving the inverse kinematics in the cases of singular pure elongation. In this work, a model-free intelligent kinematic control strategy is proposed for these problems that exhibit a mapping relationship between the output end-effector position and the input pressure. For multiple-degree-of-freedom robots, especially pneumatic soft manipulators, traditional inverse kinematic modeling methods are complex and inverse Jacobian matrix solution often encounters geometric singularities. To address this issue, this paper proposes an inverse kinematics–multilayer perceptron (IK-MLP) method for soft manipulators. In this strategy, the trained intelligent controller can be applied to control pneumatic manipulators without establishing a traditional inverse kinematic model. The control algorithm is experimentally tested based on the ground experiment system of the space soft manipulator. Simulations and experiments are carried out to validate the given model-free intelligent controller, proving that the IK-MLP method can effectively solve the singularity of inverse kinematics.

Linear Model of Inverse Kinematics for Non-Orthogonal Shafting Laser Theodolite

Linear Model of Inverse Kinematics for Non-Orthogonal Shafting Laser Theodolite

Uključivanje kretanja gornje i donje platforme - generalizovani inverzni kinematički model za simulaciju i eksperimentalno testiranje 6-ups Stjuart platforme

Due to accuracy and precision of parallel manipulators like Stewart platform, several technological applications have relied on them. An accurate kinematic model must be developed in order to improve the manipulator's accuracy. In this paper, inverse kinematic model investigation and verification have been accomplished. Conducting both upper and lower platforms under various motion types is a defining feature of this model. The 3D model of the platform has been directly linked to SimMechanics, paving the way for simulation analysis. MATLAB was used to code the obtained kinematic model. Workspace analysis of the platform has shown the permissible 3D range of each leg, and its intersection consists the total range of the upper platform. Simulation analysis has shown that, position track error hadn't exceeded 10% along any axis, while orientation error hadn't exceeded 2.32% about any axis. In the Experimental model test, the total average error in actuator's displacements is 0.094 cm, while the total average error in rotation angles is 1.145° .

Analysis of Repetitive Positioning Accuracy of Parallel Mechanisms Based on Monte Carlo Method

Based on the inverse kinematics model of the Stewart parallel mechanism, a motion platform pose error model was constructed through differential transformation. The error model shows that the motion platform pose error comes from the length error of 6 struts and the position error of 12 hinge centers, with a total of 42 error terms. Monte Carlo simulation was used to analyze the effects of struts length error on the pose error of the moving platform. The results show that when the length error of the struts follows a normal distribution, the posture error of the moving platform approximately follows a normal distribution. Monte Carlo simulation is a highly effective error analysis method that can analyze the error distribution pattern of the mechanism before processing and assembly, which provides a method for error analysis of Stewart parallel mechanisms.

Inverse Kinematics Model For a 18 Degrees of Freedom Robot

The study of humanoid robots is still a challenge for the scientific community, although there are several related works in this area, several limitations have been found in the literature that drive the need to develop an inverse kinematic modeling of biped robots. This paper presents a research proposal for the Bioloid Premium robot. The objective is to propose a complete solution to the inverse kinematics model for a 18 DOF (Degrees Of Freedom) biped robot. This model will serve as a starting point to obtain the dynamic model of the robot in a subsequent work. The proposed methodology can be extended to other biped robots.

Inverse Kinematics Model For a 18 Degrees of Freedom Robot

The study of humanoid robots is still a challenge for the scientific community, although there are several related works in this area, several limitations have been found in the literature that drive the need to develop an inverse kinematic modeling of biped robots. This paper presents a research proposal for the Bioloid Premium robot. The objective is to propose a complete solution to the inverse kinematics model for a 18 DOF (Degrees Of Freedom) biped robot. This model will serve as a starting point to obtain the dynamic model of the robot in a subsequent work. The proposed methodology can be extended to other biped robots.

Inverse Kinematics Model For a 18 Degrees of Freedom Robot

The study of humanoid robots is still a challenge for the scientific community, although there are several related works in this area, several limitations have been found in the literature that drive the need to develop an inverse kinematic modeling of biped robots. This paper presents a research proposal for the Bioloid Premium robot. The objective is to propose a complete solution to the inverse kinematics model for a 18 DOF (Degrees Of Freedom) biped robot. This model will serve as a starting point to obtain the dynamic model of the robot in a subsequent work. The proposed methodology can be extended to other biped robots.

Gain scheduled task space control of multi DOF machine tools with non-linear parallel kinematics

Machine tools with multiple degrees of freedom and parallel kinematics offer tremendous opportunities for new kind of processes but at the same time also a lot of control challenges. They are subject to uncertainties in the form of kinematic errors, elasticities and thermal deflections. Their kinematic non-linearity requires the application of model-based control concepts whose full effectiveness can only be unlocked through controls in the task space. In particular, kinematic singularities occur in forming machines such as presses, which make closed-loop control at corresponding operating points considerably more difficult. In this paper, we use the example of a servo-driven press with three ram degrees of freedom to show how parallel kinematic machine tools can be controlled via inverse differential kinematics models in task space and to what extent the controls can benefit from scheduled gain factors. The results are validated both simulatively and experimentally. In the experimental tests, three-dimensional tool paths are traced that can be used to carry out orbital forging processes. Furthermore, the example of a punch hole rolling process demonstrates that the ram pose is controlled more accurately, which also has positive effects on the resulting workpiece geometry. The performance of the developed gain scheduling task space control is compared with that of a robust and non-robust control with static gains.

A dual-loop feedback trajectory tracking control for rock drilling hydraulically driven manipulator

This paper is devoted to proposing a feedback trajectory tracking control method for hydraulically driven rock drilling robotic manipulators. The rock drilling robot has a large-scale long boom and multiple joints (6R-2P), so the deformation of the arm may not be neglected. A kinematic model with the flexible deformation of the boom is developed by adding a modified coordinate transformation matrix to the general model. Each joint motion is determined by solving the inverse kinematic model in an optimization algorithm, which aims at minimizing the positional error and smoothing the motion. A dual-loop feedback controller is proposed to track the end-effector’s position and orientation. Based on the model predictive control (MPC) method, the inner-loop controller controls the cylinder motion by controlling the cylinder motion. The outer-loop controller uses the fuzzy-PID control to correct the position error which is caused by the inner-loop controller. Several reference trajectories are designed to validate the effectiveness of the proposed dual-loop control strategy, which demonstrates it has higher accuracy and lower control fluctuation than single-loop and other dual-loop controllers.

Compact Design and Task Space Control of a Robotic Transcatheter Delivery System for Mitral Valve Implant.

Mitral regurgitation (MR) is one of the most common valvular abnormalities, and the gold-standard for treatment is surgical mitral valve repair/replacement. Most patients with severe MR are over the age of 75, which makes open-heart surgery challenging. Thus, minimally invasive surgeries using transcatheter approaches are gaining popularity. This paper proposes the next generation of a robotic transcatheter delivery system for the mitral valve implant that focuses on the design of the actuation system, modeling, and task space control. The proposed actuation system is compact while still enabling bidirectional torsion, bending, and prismatic joint motion. A pulley structure is employed to actuate the torsion and bending joints using only one motor per joint in conjunction with an antagonistic passive spring to reduce tendon slack. The robotic transcatheter is also optimized to increase its stability and reduce bending deflection. An inverse kinematics model (with an optimization algorithm), singularity analysis method, and joint hysteresis and compensation model are developed and verified. Finally, a task space controller is also proposed. Experiments, including trajectory tracking and demonstrations of the robot motion in an ex vivo porcine heart and a phantom heart through a tortuous path are presented.

Inverse Kinematic Modeling of the Tendon-Actuated Medical Continuum Manipulator Based on a Lightweight Timing Input Neural Network

Inverse Kinematic Modeling of the Tendon-Actuated Medical Continuum Manipulator Based on a Lightweight Timing Input Neural Network

A design of 2-DoFs spherical parallel manipulator with adjustable workspace

Spherical parallel manipulators (SPMs) have promising industrial applications due to their strong mechanical performance. However, they face challenges such as singularity avoidance, tight tolerance manufacturing requirements, and the need for versatile and dexterous end-effector functionalities. Additionally, SPMs lack customizability due to singularity and collision issues. This work introduces a novel design principle that addresses these challenges by benchmarking two analytical methods: structural synthesis using screw theory and dimensional synthesis using dimensionless parameters. A proof of concept of a 2-DoF SPM that can operate within a cylindrical constraint and realize a full workspace without collision is presented. This design allows for adjustable reachable workspace at the end-effector, despite significant geometric constraints. These findings on mechanical design solutions provide customizability for SPMs, and a 3D model with an aspect ratio of 1/12 is presented and discussed for potential practical applications. Overall, it is identified that both a simulation using Recurdyn and inverse kinematic model show the desired movements at the moving platform with the maximum error of 0.0013°.

Development of an automatic control system for a hydraulic pruning robot

Automatic pruning is capable of trimming trees into complex shapes efficiently and continuously. However, this technology faces more challenges under unstructured agricultural environments. In the present paper, we describe the development of a hydraulic disc-saw mounted pruning robot with a relatively low cost for automated geometric pruning of fruit trees based on a new automatic pruning scenario. A pruning control strategy based on rolling observations and continuous prediction algorithm was designed to precisely control the motion of hydraulic cylinders. A forward kinematic model was described using modified Denavit–Hartenberg (D-H) notation, and the accessible workspace for the end-effector was analyzed in the simulation. The inverse kinematics model based on geometry was established, which provided the foundation for the development of a control system together with the forward kinematics model. Performance tests showed a sufficient control accuracy within ± 1.8° of all cylinders. The results of the waypoint tracking tests suggest that an increase in the step-size from 20 mm to 60 mm not only increases the moving speed and improves tracking accuracy, but also increases the fluctuation of the end-effector in the Z-axis direction. The movement of the chassis can introduce new errors and results in a larger average absolute positional error along the X-axis. The average startup and stop lag of the control system was 0.55 s and 0.15 s, respectively. This study provides guidance for pruning robot path planning and lays the foundation for future iterations of autonomous pruning robots.

A Forward Solution Algorithm of 6RUS Parallel Mechanism Based on Dual Quaternion Method

The 6RUS parallel manipulator is a highly versatile and widely used robotic mechanism with six degrees of freedom. Its intricate kinematic structure and its capability to perform complex motion tasks have garnered significant research interest in recent years. The kinematic analysis of the 6RUS mechanism plays a crucial role in understanding its operational characteristics and optimizing its performance for various applications. In this paper, we present a state-of-the-art kinematic algorithm for the 6RUS parallel manipulator. Our algorithm is aimed at addressing the challenges associated with accurately determining the pose and motion of the end-effector relative to the base, considering the complexity of the mechanism’s architecture. By leveraging advanced mathematical modeling techniques and utilizing efficient computational algorithms, our proposed algorithm offers improved accuracy, efficiency, and robustness in determining the kinematic parameters of the 6RUS mechanism. The key contributions of this work include the development of a comprehensive forward and inverse kinematic model for the 6RUS parallel manipulator, incorporating the effects of joint constraints, singularities, and workspace limitations. We also present a detailed analysis of the algorithm’s performance in comparison to existing approaches, demonstrating its superiority in terms of computational efficiency and accuracy. The proposed kinematic algorithm holds significant potential for enhancing the design, control, and trajectory planning of 6RUS parallel manipulators. It provides a solid foundation for advanced applications such as robotic surgery, industrial automation, and virtual reality systems. The results presented in this paper contribute to the growing body of knowledge in parallel manipulator research and pave the way for future developments in the field.

Design of an optimized gait planning generator for a quadruped robot using the decision tree and random forest workspace model

AbstractReal-time gait trajectory planning is challenging for legged robots walking on unknown terrain. In this paper, to realize a more efficient and faster motion control of a quadrupedal robot, we propose an optimized gait planning generator (GPG) based on the decision tree (DT) and random forest (RF) model of the robot leg workspace. First, the framework of this embedded GPG and some of the modules associated with it are illustrated. Aiming at the leg workspace model described by DT and RF used in GPG, this paper introduces in detail how to collect the original data needed for training the model and puts forward an Interpolation Labeling with Dilation and Erosion (ILDE) data processing algorithm. After the DT and RF models are trained, we preliminarily evaluate their performance. We then present how these models can be used to predict the location relation between a spatial point and the leg workspace based on its distributional features. The DT model takes only 0.00011 s to process a sample, while the RF model can give the prediction probability. As a complement, the PID inverse kinematic model used in GPG is also mentioned. Finally, the optimized GPG is tested during a real-time single-leg trajectory planning experiment and an unknown terrain recognition simulation of a virtual quadrupedal robot. According to the test results, the GPG shows a remarkable rapidity for processing large-scale data in the gait trajectory planning tasks, and the results can prove it has an application value for quadruped robot control.

Kinematic Modelling of a 3RRR Planar Parallel Robot Using Genetic Algorithms and Neural Networks

Kinematic modelling of parallel manipulators poses significant challenges due to the absence of analytical solutions for the Forward Kinematics (FK) problem. This study centres on a specific parallel planar robot, specifically a 3RRR configuration, and addresses the FK problem through two distinct methodologies: Genetic Algorithms (GA) and Neural Networks (NN). Utilising the Inverse Kinematic (IK) model, which is readily obtainable, both GA and NN techniques are implemented without the need for closed-loop formulations or non-systematic mathematical tools, allowing for easy extension to other robot types. A comparative analysis against an existing numerical method demonstrates that the proposed methodologies yield comparable or superior performance in terms of accuracy and time, all while reducing development costs. Despite GA’s time consumption limitations, it excels in path planning, whereas NN delivers precise results unaffected by stochastic elements. These results underscore the feasibility of using neural networks and genetic algorithms as viable alternatives for real-time kinematic modelling of robots when closed-form solutions are unavailable.

Design and Implementation of a 3RRR Parallel Planar Robot

Parallel manipulators have a rigid structure and can pick up heavy objects. Therefore, a parallel manipulator has been developed based on the cooperation of three arms of a robotic system to make the whole system suitable for solving many problems such as materials handling and industrial automation. The three revolute joints are used to achieve the mechanism operation of the parallel planar robot. Those revolute joints are geometrically designed using an open-loop spatial robotic platform. In this paper, the geometric structure with three revolute joints is used to drive and analyze the inverse kinematic model for the 3RRR parallel planar robot. In the proposed design, three main variables are considered: the length of links of the 3RRR parallel planar robot, the base positions of the platform, and the joint angles’ geometry. Cayley-Menger determinants and bilateration are proposed to calculate these three variables to determine the final position of the platform and to move specific objects according to given desired trajectories. The proposed structure of the 3RRR parallel planar robot is simulated and different desired trajectories are tested to study the performance of the proposed stricter. Furthermore, the hardware implementation of the proposed structure is accomplished to validate the design in practical terms.

Inverse kinematic analysis and agile control of a magnetically actuated catheter

In recent years, there has been a growing application of robotic-assisted magnetic actuation systems in the treatment of cardiovascular diseases because of the fast response and the miniaturization of medical tools. However, inverse kinematic (IK) modeling in permanent magnet systems is still a challenging task due to the complexity of the magneto-solid strong coupling field. In this paper, we present a magnetic actuation system that uses the rotation of a single permanent magnet to steer the intravascular catheter. The main contribution is the proposal of an IK modeling method that establishes a relationship between the catheter's deflection angle and the rotation angle of the driving magnet (DM). Our proposed method uses the constant curvature model (CCM) to decouple the catheter's deformation and the magnetic loads, thus enabling the efficient estimation of the position of the catheter's tip based on the desired deflection angle. After establishing the equilibrium equation, we employ a numerical computation method to optimize the rotation angle of the DM. To facilitate fast convergence, we propose an analytical solution to determine the optimal initial value. Our proposed IK modeling method has been proven to be effective in the model validation experiment, which achieves a good balance between accuracy and efficiency. The difference between the planned and actual deflection angle is 4.55±3.44° and the distal position error is 1.26±0.74 mm. The completion time of our IK method is 1–4 ms. The performance of our magnetic actuation system has been evaluated in the phantom experiment, in which the catheter can pass sequentially through the planned bifurcations and finally reach all the goals under the magnetic guidance.

A Tremor Suppression and Noise Removal Algorithm for Microscopic Robot-Assisted Cataract Surgery

Ophthalmic surgery consists of a series of precise manipulations performed using a surgical microscope. A surgical robot with a master–slave paradigm is commonly adopted to improve the precision and guidance intelligence for ophthalmic surgery; however, the surgeon's hand tremor, misoperation, inherent characteristics of the robot, and environmental interference may cause tremors of the end-effector of the surgical manipulator, thus increasing the risk of soft tissue damage and poor prognosis for the patient. A symmetrical threshold noise reduction combiner (STIC) is proposed to suppress hand tremors and reduce environmental noise interference. Additionally, the inverse kinematic model of the eight-degrees-of-freedom surgical robot for cataract surgery is developed, with the constraints of continuous circular capsulorhexis manipulation. Simulation results show that the signal-to-noise ratio of the STIC is increased from 35.3907 to 57.0158 dB, whereas the maximum, average, standard deviation, and root mean square of the output of the STIC are decreased by 64.79%, 77.24%, 74.50%, and 75.86%, respectively. Three sets of in vitro experimental results show that these four indicators of the STIC performance are reduced by 59.73%, 76.57%, 57.23%, and 65.02%, respectively. These results validate the feasibility and effectiveness of the proposed method on hand tremor suppression and inherent high-frequency disturbance elimination, thereby enhancing the accuracy of the microsurgical operation.