Inverse Kinematics Research Articles

Using Genetic Algorithms and Bézier Curves for Automatic Path Optimization of a 6-DOF Robot

This paper describes a novel method for automatically planning point-to-point motion paths for a robot with six degrees of freedom (6-DOF). A linear motion path between two points on such robots may be impractical due to joint angle constraints or exceeding the manipulator's operational range. The proposed method employs a genetic algorithm to generate suitable motion paths based on the second-, third-, and fourth-orders of Bézier curves. The control points of Bézier curves are determined using a genetic algorithm, which can adjust the fitness function as the end-effector moves closer to the obstacle. As a result, the algorithm can adjust its motion path planning in response to obstacles. The motion paths are generated with the goal of optimizing the robot's inverse kinematic configuration. The results show that using a genetic algorithm and Bézier curves can produce motion paths with smooth transitions, minimal changes in joint angles, and no sudden jerks within the robot's operational area in both obstacle-free and obstacle avoidance scenarios. This solution may be useful for intelligent robots with automated path-planning capabilities in unknown environments.

Solving the redundant inverse kinematics of hyper rope-driven snake-shaped manipulator using an improved hunter–prey optimizer algorithm

Solving the redundant inverse kinematics of hyper rope-driven snake-shaped manipulator using an improved hunter–prey optimizer algorithm

Forward and inverse kinematics of a 6-DOF robotic manipulator with a prismatic joint using MATLAB robotics toolbox

Forward and inverse kinematics of a 6-DOF robotic manipulator with a prismatic joint using MATLAB robotics toolbox

Optimizing PID control for enhanced stability of a 16‐DOF biped robot during ditch crossing

AbstractThe current research article discusses the design of a proportional–integral–derivative (PID) controller to obtain the optimal gait planning algorithm for a 16‐degrees‐of‐freedom biped robot while crossing the ditch. The gait planning algorithm integrates an initial posture, position, and desired trajectories of the robot's wrist, hip, and foot. A cubic polynomial trajectory is assigned for wrist, hip, and foot trajectories to generate the motion. The foot and wrist joint angles of the biped robot along the polynomial trajectory are obtained by using the inverse kinematics approach. Moreover, the dynamic balance margin was estimated by using the concept of the zero‐moment point. To enhance the smooth motion of the gait planner and reduce the error between two consecutive joint angles, the authors designed a PID controller for each joint of the biped robot. To design a PID controller, the dynamics of the biped robot are essential, and it was obtained using the Lagrange–Euler formulation. The gains, that is, KP, KD, and KI of the PID controller are tuned with nontraditional optimization algorithms, such as particle swarm optimization (PSO), differential evolution (DE), and compared with modified chaotic invasive weed optimization (MCIWO) algorithms. The result indicates that the MCIWO‐PID controller generates more dynamically balanced gaits when compared with the DE and PSO‐PID controllers.

Research on Motion Control and Compensation of UAV Shipborne Autonomous Landing Platform

As an important interface between unmanned aerial vehicles (UAVs) and ships, the stability and motion control compensation technology of the shipborne UAV landing platform are paramount for successful UAV landings. This paper has designed a new control compensation method for an autonomous UAV landing platform to address the impact of complex sea conditions on the stability of UAV landing platforms. Firstly, the parallel Stewart platform was introduced as the landing platform, and its structure was analyzed with forward and inverse kinematic calculations conducted in Matlab to verify its accuracy. Secondly, a least-squares recursive AR prediction algorithm was designed to predict the future attitudes of ships under varying sea conditions. Finally, the prediction algorithm was combined with the platform’s control strategy and a dual-sensor system was adopted to ensure the stability of the UAV landing process. The experimental results demonstrate that these innovative improvements enhanced the compensation accuracy by 59.6%, 60.3%, 48.4%, and 47.9% for the rolling angles of 5° and 10° and the pitching angles of 5° and 10°, respectively. Additionally, the compensation accuracy for the roll and pitch in sea states 2 and 5 improved by 51.2%, 59.4%, 58.7%, and 55.9%, respectively, providing technical support for UAV missions such as maritime rescue and exploration.

Human-redundant robot interaction and redundancy utilization based on three-dimensional force sensor

To make full use of redundant characteristics, the inverse kinematics algorithm based on augmented Jacobian matrix with the goal of avoiding joint limit and obstacle is adopted. Then, admittance control system is established for human-robot interaction, and force control is converted into motion control of robot. Through the expansion of Jacobian matrix, the model of joint limit avoidance is established. Regarding obstacle avoidance in human-robot interaction process, the potential function gradient is calculated and augmented Jacobian matrix is formed. Thus, comprehensive control model of human-robot interaction and obstacle avoidance is established. When the external force is applied, the robot can move smoothly along the human hand. The robot's motion process is smooth and compliant. At the same time, when performing task of avoiding joint limit, the values of the joint angle are within the set range. The average angle margin of the four joints is over 60 %. So the goal of avoiding the joint limit is achieved. When adding obstacle avoidance in the interaction control, the difference value between the minimum distance and safe distance is always positive. The safety margin of the distance is over 20 %. So the robot does not contact with the obstacle. So human-robot interaction and redundancy utilization can be realized simultaneously.

Comparative Analysis of Structure and Motion of Vision Logistics Robotic Arms

This paper combines visual recognition and robotic arm, optimizes the design of robotic arm structure, and researches the logistics robotic arm with six degrees of freedom and visual perception ability to enrich the logistics robotic use scene. Firstly, the visual recognition system is installed on the existing six-degree-of-freedom robotic arm, and the coordinate system is established by the light bar recognition method combined with the D-H parameter method. Secondly, a kinematic simulation model was established by using MATLAB, and the state of the joints was analyzed by using forward and inverse kinematic simulation and fifth degree polynomial interpolation. Finally, the actual logistics fixed-point transportation task is designed for trajectory planning. The results show that the robotic arm is able to be able to perform different grasping tasks in non-structural environments, around the visual analysis of the robotic arm as well as the optimization of the motion track, to enhance the efficiency of the comprehensive use of visual and tactile information, to improve the adaptability of the robotic hand grasping, and to be able to meet the precise control of the pick-up process and the use of the realization of the payload grasping and dexterous movement. The research in this paper provides a certain reference value for the propulsion robot arm to perform intelligent grasping tasks.

Designing and Creating a Palletizing Robot Conbined with Image Processing

In this paper, we propose a solution of designing and building a three-order 4D magician robot arm to palletize goods. Inverse kinematic of system is calculated. Thence, we design a suitable robot arm which can utilizing camera to palletizing goods. PID controller is used to move operating point. Simulation and experimental results are shown to prove the well operation of this robot arm.

Artificial Neural Network-based Approach for Inverse Kinematics of PUMA 260 Robot

Artificial Neural Network-based Approach for Inverse Kinematics of PUMA 260 Robot

Design, Analysis and Experiment of a Modular Deployable Continuum Robot

Continuum robots, possessing great flexibility, can accomplish tasks in complex work scenes, regarded as an important direction in robotics. However, the current continuum robots are not satisfying enough in terms of fabrication and maintenance, and their workspace is limited by structure and other aspects. In this paper, to address the above problems, a modular deployable robot, which adopts an origami structure instead of a flexible hinge, is proposed. A fabrication method is innovated, the Spherical Linkage Parallel Mechanism (SLPM) unit is optimized, and the installation and fabrication process of the robot is simplified through modularization. The forward kinematics and inverse kinematics of the robot and its workspace are analyzed by using the screw theory. The prototype of the robot is constructed, and its folding performance, bending performance, and motion accuracy are tested, and the error analysis and compensation optimization are carried out. After the optimization, the position error of the robot is reduced by about 65%, and the standard deviation is greatly lowered, which effectively improves the motion accuracy and stability of the robot.

Design and Control of a Novel 6-DOF Desktop Upper Limb Rehabilitation Robot

Abstract This paper presents the design, analysis, and development of a Novel six degrees of freedom (6-DOF) desktop upper limb rehabilitation robot. The upper limb rehabilitation robot is mainly composed of the Omnidirectional mobile platform, armrest, and 3-DOF wrist rehabilitation mechanism. The forward and inverse kinematics and Jacobian matrix of the upper limb rehabilitation robot are derived based on the kinematics of a rigid body, and its working space is analyzed based on arm kinematics as well. The forward and inverse kinematics of the arm are derived based on the D-H method. A new control strategy and control algorithm were developed based on the hardware structure of the robot system and arm model, and the control strategy and control algorithm are used to carry out the simulated rehabilitation experiment on a single joint of the arm and the simulated rehabilitation experiment on multiple joint linkages in the arm. The experimental results show that the maximum error in the simulated rehabilitation experiment on a single joint of the arm is 6.123 deg, and the maximum error in the simulated rehabilitation experiment of multiple joint linkages in the arm is 5.323 deg. Therefore, the control strategy and control algorithm can complete the corresponding rehabilitation training. This 6-DOF desktop upper limb rehabilitation robot can provide passive rehabilitation training for patients in the early stages of paralysis.

Kinematics analysis and simulation of bionic five-finger manipulator

Abstract To address the complexity of traditional manipulator structures, a bionic five-finger manipulator has been designed and developed. After introducing the manipulator’s structure and functionality, the kinematic model was established using the D-H parameter method, followed by the analysis of forward and inverse kinematics. The fingertip pose was derived using the homogeneous transformation formula, and the accuracy of the theoretical analysis was validated by comparing the mathematical and MATLAB simulation results. The Monte Carlo method was employed to determine the accessible motion space of the mechanical fingertip. Subsequently, trajectory planning for the manipulator was performed based on known initial and end finger angles. A comparison with ADAMS simulation results demonstrated the rationality of the mechanical finger’s movement space, stable speed, and compliance with actual grasping requirements. This study lays a theoretical foundation for the subsequent parameter optimization of the manipulator.

Research on Inverse Kinematics of Redundant Robotic Arms Based on Flexibility Index

Research on Inverse Kinematics of Redundant Robotic Arms Based on Flexibility Index

Analytical Inverse Kinematics for 2-Segment Extensible Continuum Manipulators

Abstract Fast inverse kinematics (IK) algorithm is significant for real-time precise motion control of continuum and soft manipulator. In this paper, we studied an explicit expression of two-segment continuum manipulator based on the constant curvature assumptions and discussed the existence of the IK solutions. This model used pseudo-rigid-body method, unlike 6-axis rigid industrial robot arm, we found that the two-segment extensible continuum manipulators have limited rotation angle around the direction vector of its tip, i.e., this type manipulator has limited dexterity. Then we pre-constrained five degrees of freedom (DOFs) constrained and discussed the definition of the left DOF. The IK solving process is simplified to realize small calculation cost for most applications. This model will provide a robust and real-time way to control the two-segment extensible continuum manipulators.

Design, Analysis and Optimization of Four Degrees of Freedom of Parallel Gripper Mechanism for Industrial Automation

Objectives: To obtain the positions, velocities, and acceleration of actuators of the 4-DOF of the parallel gripper, and optimization of the mechanism is carried out to find the optimal dimensions of the mechanism. Methods: Kinematic analysis is carried out to find the positions and velocities of the gripper of the mechanism. The method used to solve the position of the mechanism is inverse kinematics. A source code is written in MATLAB software to find the positions and velocities of the gripper. This software is a computing platform which can solve large size matrices easily which is most suitable for robots. A model of the mechanism is created in CATIA with constraints. The developed CATIA model is used in ANSYS software for structural analysis. The method used for finding optimal dimensions is Genetic algorithms. Optimization is carried out using Genetic Algorithms (GA’s) using the Energy Manipulation Index as an objective for obtaining the optimal dimensions of the parallel gripper mechanism. Finally, ADAMs software is used to simulate the mechanism. Findings: using inverse kinematic equations the results of displacements, velocities, and accelerations obtained for in-plane horizontal motion, and in-plane vertical motion s plotted. After checking the gripper performance, It is observed that the in-plane vertical transmission is better than the in-plane horizontal transmission. Based on the Energy Manipulation Index (EMI), the performance-to-effort ratio of the gripper object is calculated. It tells about the physical significance of energy transfer efficiency. If the energy occupied by the end-effector is higher than the 4-DOF Parallel Gripper achieves higher efficiency and possesses better manipulability performance. Maximum EMI is taken as an objective for optimization using GA. Simulation is carried out using ADAMS software to determine the driving forces or torques. Novelty/improvement: In this paper the performance index EMI is taken as objective to find the optimal dimensions of the 4-DOF of parallel gripper. Keywords: ­ DOF parallel gripper, In­hand manipulation, In­hand twisting, Driving force, Energy Manipulation Index (EMI)

Validation of IMU against optical reference and development of open-source pipeline: proof of concept case report in a participant with transfemoral amputation fitted with a Percutaneous Osseointegrated Implant

BackgroundSystems that capture motion under laboratory conditions limit validity in real-world environments. Mobile motion capture solutions such as Inertial Measurement Units (IMUs) can progress our understanding of "real" human movement. IMU data must be validated in each application to interpret with clinical applicability; this is particularly true for diverse populations. Our IMU analysis method builds on the OpenSim IMU Inverse Kinematics toolkit integrating the Versatile Quaternion-based Filter and incorporates realistic constraints to the underlying biomechanical model. We validate our processing method against the reference standard optical motion capture in a case report with participants with transfemoral amputation fitted with a Percutaneous Osseointegrated Implant (POI) and without amputation walking over level ground. We hypothesis that by using this novel pipeline, we can validate IMU motion capture data, to a clinically acceptable degree.ResultsAverage RMSE (across all joints) between the two systems from the participant with a unilateral transfemoral amputation (TFA) on the amputated and the intact sides were 2.35° (IQR = 1.45°) and 3.59° (IQR = 2.00°) respectively. Equivalent results in the non-amputated participant were 2.26° (IQR = 1.08°). Joint level average RMSE between the two systems from the TFA ranged from 1.66° to 3.82° and from 1.21° to 5.46° in the non-amputated participant. In plane average RMSE between the two systems from the TFA ranged from 2.17° (coronal) to 3.91° (sagittal) and from 1.96° (transverse) to 2.32° (sagittal) in the non-amputated participant. Coefficients of Multiple Correlation (CMC) results between the two systems in the TFA ranged from 0.74 to > 0.99 and from 0.72 to > 0.99 in the non-amputated participant and resulted in ‘excellent’ similarity in each data set average, in every plane and at all joint levels. Normalized RMSE between the two systems from the TFA ranged from 3.40% (knee level) to 54.54% (pelvis level) and from 2.18% to 36.01% in the non-amputated participant.ConclusionsWe offer a modular processing pipeline that enables the addition of extra layers, facilitates changes to the underlying biomechanical model, and can accept raw IMU data from any vendor. We successfully validate the pipeline using data, for the first time, from a TFA participant using a POI and have proved our hypothesis.

Using Particle Filters to Solve the Problem of Symmetric Multiple Solutions in Robot Inverse Kinematics

Using Particle Filters to Solve the Problem of Symmetric Multiple Solutions in Robot Inverse Kinematics

An Efficient Quadratic Programming Method for Kinematic Control of Redundant Manipulators under Joint Velocity Constraints

This paper presents an efficient inverse kinematics solution for redundant robotic arms. The proposed method combines the principles of continuation methods, improves the instability of the computation time by increasing the convergence of the kinematics function, and improves the efficiency of traditional numerical methods. The effectiveness and efficient performance of the method are demonstrated through comparative experiments. The computational speed of the method is twice as fast as the Newton–Raphson method under joint limit constraints and equal solution accuracy.

Industrial Robot Trajectory Optimization Based on Improved Sparrow Search Algorithm

This paper proposes an enhanced multi-strategy sparrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressing issues of low efficiency and high vibration impact on joints during operation. Initially, the improved D-H parametric method is employed to establish both forward and inverse kinematic models of the robot. Subsequently, a 3-5-3 mixed polynomial interpolation trajectory planning approach is applied to the robot. Building upon the conventional sparrow algorithm, a two-dimensional Logistic chaotic system initializes the population. Additionally, a Levy flight strategy and nonlinear adaptive weighting are introduced to refine the discoverer position update operator, while an inverse learning strategy enhances the vigilante position update operator. These modifications boost both the local and global search capabilities of the algorithm. The improved sparrow algorithm, based on 3-5-3 hybrid polynomial trajectory planning, is then used for the time-optimal trajectory planning of the robot. This is compared with traditional sparrow search algorithm and particle swarm algorithm optimization results. The findings indicate that the proposed enhanced sparrow search algorithm outperforms both the standard sparrow algorithm and the particle swarm algorithm in terms of convergence speed and accuracy for robot trajectory optimization. This can lead to the increased work efficiency and performance of the robot.

Noise suppression zeroing neural network for online solving the time-varying inverse kinematics problem of four-wheel mobile manipulators with external disturbances

A novel noise suppression zeroing neural network (NSZNN) is presented for the trajectory tracking problem on a four Mecanum wheeled mobile manipulator (FMWMM) by solving its time-varying inverse kinematics (TVIK) problem. The holistic kinematic model of the FMWMM is developed, which can receive synergistic control of the mobile manipulator. Different from the situation without external interference addressed in our previous work, this paper considers a variety of common time-varying interferences by studying the basic principles of various noises, and proves the NSZNN model’s of the validity and superiority, which solves the TVIK problem of the FMWMM with external disturbances through theoretical analyses. Compared with the existing gradient neural network (GNN) and the traditional zeroing neural network (ZNN), the most representative hybrid noise is selected to conduct a large number of experiments to substantiate the high efficiency and robustness of the NSZNN model. Finally, the NSZNN model is verified on the FMWMM via a robot operating system (ROS) by a successful execution of the trajectory tracking task.