Inverse Kinematics Method Research Articles

Novel thick-target inverse kinematics method for the astrophysical 12C+12C fusion reaction

Novel thick-target inverse kinematics method for the astrophysical 12C+12C fusion reaction

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.

A form-finding method for deployable tensegrity arms and inverse kinematics

A form-finding method for deployable tensegrity arms and inverse kinematics

A Closed-Form Inverse Kinematic Analytical Method for Seven-DOF Space Manipulator with Aspheric Wrist Structure

The seven-degree-of-freedom space manipulator, characterized by its redundant and aspheric wrist structure, is extensively used in space missions due to its exceptional dexterity and multi-joint capabilities. However, the non-spherical wrist structure presents challenges in solving inverse kinematics, as it cannot decouple joints using the Pieper criterion, unlike spherical wrist structures. To address this issue, this paper presents a closed-form analytical method for solving the inverse kinematics of seven-degree-of-freedom aspheric wrist space manipulators. The method begins by identifying the redundant joint through comparing the volumes of the workspace with different joints fixed. The redundant joint angle is then treated as a parametric joint angle, enabling the derivation of closed-form expressions for the non-parametric joint angles using screw theory. The optimal solution branch is identified through a comparative analysis of various self-motion manifold branches. Additionally, a hybrid approach, combining analytical and numerical methods, is proposed to optimize the parametric joint angle for a trajectory tracking task. Simulation results confirm the effectiveness of the proposed method.

Protein folding, protein dynamics and the topology of self-motions.

It has long been recognized that segments of the protein main chain are like robotic manipulators and inverse kinematics methods from robotics have been applied to model loops to bridge gaps in protein comparative modelling. The complex internal motion of a redundant manipulator with fixed ends is called a self-motion and its character is determined by the relative position of its ends. Self-motions that are topologically equivalent (homotopic) occupy the same continous region of the configuration space. Topologically inequivalent (non-homotopic) regions are separated by co-regular surfaces and crossing a co-regular surface can result in a sudden dramatic change in the character of the self-motion. It is shown, using a five-residue type I β-turn, that these concepts apply to protein segments and that as the ends of the five-residue segment come closer together, a co-regular surface is crossed, and the structure is locked in to becoming either a type I or type I' turn. It is also shown that the type II turn is topologically equivalent to the type I' turn, not the type I turn. These results have implications for both native-state protein dynamics and protein folding.

Intelligent Rock-Climbing Robot Capable of Multimodal Locomotion and Hybrid Bioinspired Attachment.

Rock-climbing robots have significant potential in fieldwork and planetary exploration. However, they currently face limitations such as a lack of stability and adaptability on extreme terrains, slow locomotion, and single functionality. This study introduces a novel multimodal and adaptive rock-climbing robot (MARCBot), which addresses these limitations through spiny grippers that draw inspiration from morpho-functionalities observed in beetles, arboreal birds, and hoofed animals. This hybrid bioinspired design enables high attachment strength, passive adaptability to different terrains, and quick attachment on rock surfaces. The multimodal functionality of the gripper allows for attachment during climbing and support during walking. A novel control strategy using dynamics and quadratic programming (QP) optimizes attachment wrench distribution, reducing cost-of-transport by 20.03% and 6.05% compared to closed-loop inverse kinematic (CLIK) and virtual model control (VMC) methods, respectively. MARCBot achieved climbing speeds of 0.15mmin-1 on a vertical discrete rock surface under gravity and trotting speeds of up to 0.21ms-1 on various complex terrains. It is the first robot capable of climbing on rock surfaces and trotting in complex terrains without the need for switching end-effectors. This study highlights significant advancements in climbing and multimodal locomotion for robots in extreme environments.

A Novel Cost Calculation Method for Manipulator Trajectory Planning.

It is worthwhile to calculate the execution cost of a manipulator for selecting a planning algorithm to generate trajectories, especially for an agricultural robot. Although there are various off-the-shelf trajectory planning methods, such as pursuing the shortest stroke or the smallest time cost, they often do not consider factors synthetically. This paper uses the state-of-the-art Python version of the Robotics Toolbox for manipulator trajectory planning instead of the traditional D-H method. We propose a cost function with mass, iteration, and residual to assess the effort of a manipulator. We realized three inverse kinematics methods (NR, GN, and LM with variants) and verified our cost function's feasibility and effectiveness. Furthermore, we compared it with state-of-the-art methods such as Double A* and MoveIt. Results show that our method is valid and stable. Moreover, we applied LM (Chan λ = 0.1) in mobile operation on our agricultural robot platform.

Impedance-based biomechanical method for robust inverse kinematics from noisy data.

This paper presents a novel method for solving the inverse kinematic problem of capturing human reaching movements using a dynamic biomechanical model. The model consists of rigid segments connected by joints and actuated by markers. The method was validated against a rotation matrix-based method using motion capture data recorded during reaching movements performed by healthy human volunteers. The results showed that the proposed method achieved low errors in joint angles and compensated for noise in motion capture data. The angles were comparable to those calculated using the standard marker-based method. The proposed bioinspired method can be used in real-time medical applications for processing noisy marker data with occlusions.

Time-optimal coordinated detumbling and pose adjusting control of a non-cooperative target with model uncertainties

In this paper, a novel post-capture takeover control strategy of non-cooperative target with model uncertainties by the dual-arm space manipulator is proposed. Two mission objectives of target detumbling and pose adjusting are comprehensively considered. First, the motion trajectory of the target is parameterized with normalized time by a Bezier shape-based function. On this basis, by considering the resultant external force and moment constraint and the model uncertainties of the target, the mission duration is optimized to obtain the time optimal detumbling and pose adjusting the trajectory of the target. Furthermore, the desired trajectory in manipulator joint space is obtained by introducing the arm angle inverse kinematics method, and a joint trajectory tracking controller is designed based on the feedback linearization theory to track the desired joint trajectory. Simulation results show that detumbling and pose adjusting can be simultaneously achieved by one control action, which verifies the effectiveness of the proposed integrated control strategy.

An efficient solver for the inverse kinematics of cable-driven manipulators with pure rolling joints using a geometric iterative approach

The inverse kinematics (IK) problem of cable-driven manipulators with pure rolling joints (CDM-PRJs) presents unique challenges due to the equal angle constraints and strict joint limits. These factors render existing IK solvers ineffective or result in substantial degradation of their performance. To address these challenges, we propose a three-phase geometric iterative method to efficiently solve the IK problem for CDM-PRJs, which is a variant of the forward and backward reaching inverse kinematics method. Our method begins by establishing a surrogate model for CDM-PRJs to handle the equal angle constraints. Subsequently, we introduce a geometric iterative approach comprising a forward reaching phase, a backward reaching phase, and a state update phase. Additionally, we devise two novel measures, the random disturbance measure and the branch change measure, to effectively address deadlock situations and asymmetric joint limits, respectively. Simulation results demonstrate that our method surpasses the inverse Jacobian method and the sequential quadratic programming method in terms of success rate and computational efficiency. Furthermore, our method exhibits generality across various CDM-PRJs.

Sagittal plane knee kinematics can be measured during activities of daily living following total knee arthroplasty with two IMU.

Knee function is rarely measured objectively during functional tasks following total knee arthroplasty. Inertial measurement units (IMU) can measure knee kinematics and range of motion (ROM) during dynamic activities and offer an easy-to-use system for knee function assessment post total knee arthroplasty. However, IMU must be validated against gold standard three-dimensional optical motion capture systems (OMC) across a range of tasks if they are to see widespread uptake. We computed knee rotations and ROM from commercial IMU sensor measurements during walking, squatting, sit-to-stand, stair ascent, and stair descent in 21 patients one-year post total knee arthroplasty using two methods: direct computation using segment orientations (r_IMU), and an IMU-driven iCloud-based interactive lower limb model (m_IMU). This cross-sectional study compared computed knee angles and ROM to a gold-standard OMC and inverse kinematics method using Pearson's correlation coefficient (R) and root-mean-square-differences (RMSD). The r_IMU and m_IMU methods estimated sagittal plane knee angles with excellent correlation (>0.95) compared to OMC for walking, squatting, sit-to-stand, and stair-ascent, and very good correlation (>0.90) for stair descent. For squatting, sit-to-stand, and walking, the mean RMSD for r_IMU and m_IMU compared to OMC were <4 degrees, < 5 degrees, and <6 degrees, respectively but higher for stair ascent and descent (~12 degrees). Frontal and transverse plane knee kinematics estimated using r_IMU and m_IMU showed poor to moderate correlation compared to OMC. There were no differences in ROM measurements during squatting, sit-to-stand, and walking across the two methods. Thus, IMUs can measure sagittal plane knee angles and ROM with high accuracy for a variety of tasks and may be a useful in-clinic tool for objective assessment of knee function following total knee arthroplasty.

Robotis Can Create Numerical Inverse Kinematic Problems Because Continuously Replace Humans

Robotic process automation is an smart way to manage work across those machines which AI can easily be categorize. Robot Automation is a sequence of steps that gives result in a meaningful action without interference of human being. robotics, design, construction, and use of machines (robots) to perform tasks done traditionally by human beings. Robots are widely used in such industries as automobile manufacture to perform simple repetitive tasks, and in industries where work must be performed in environments hazardous to humans. Medical robotics is an interdisciplinary field that focuses on developing electromechanical devices for clinical applications. The goal of this field is to enable new medical techniques by providing new capabilities to the physician or by providing assistance during surgical procedures. robotics is revolutionizing the future of work in a variety of industries. From manufacturing and logistics to healthcare and education, robots are improving efficiency, productivity, and safety. The application of the inverse kinematics method will herald a new approach in the robot nondestructive testing industry. Meanwhile, complicated matrix operations greatly limit traditional inverse kinematics methods.

Research on kinematics modeling and path planning of a hyper-redundant continuum robot

It has always been the case that work in confined spaces has high difficulty and complexity, and robots are usually required to replace humans to perform the corresponding operations. For the maintenance work in the fuel tank of a certain type of aircraft, a continuum robot with 32 staggered orthogonal joints is designed in this paper. To solve the motion problem of this robot, this paper combines the end-following method with the Jacobi inverse kinematics method, and proposes an end-following-segmented Jacobi method, which improves the accuracy and efficiency of the inverse kinematics solution. A ray path-planning algorithm for continuum robots is proposed for the job requirements of this robot and the specific operating environment inside an airplane fuel tank, and it is compared with the rapidly-exploring random trees (RRT) algorithm and particle swarm optimization (PSO) algorithm. The experimental results show that the planning time of the ray path-planning algorithm is less compared with the RRT algorithm and the PSO algorithm, and the paths obtained are shorter. Finally, a path-following simulation is performed on a 32-joint continuum robot model to verify the followability of the ray path algorithm.

Multi-stage trajectory tracking of robot manipulators under stochastic environments

For robot manipulators composed of Lagrange subsystems driven by direct current (DC) motors under stochastic environments, multi-stage trajectory tracking is investigated in this paper. The main challenge is how to achieve the end-effector drive of manipulators from a given initial state to a final state. First, the inverse kinematics method and the partition of the task space are adopted to tackle multi-stage trajectory planning. Second, the adaptive backstepping technique is used to design tracking controller for stochastic Lagrangian subsystems. Then, based on the state-dependent switching signal, a multi-stage switched controller is designed for trajectory tracking of robot manipulators. All signals in the close-loop error switched system are bounded in probability, and the tracking error in mean square can be made arbitrarily small enough by parameters-tuning The effectiveness of the proposed control method is illustrated by simulation results.

Design and implementation of a 7-DOF cable-driven serial spray-painting robot with motion-decoupling mechanisms

This paper presents the design and implementation of a 7-DOF cable-driven serial spray-painting robot (CDSSR) featuring motion-decoupling mechanisms and introduces an improved non-singular inverse kinematics method for redundant serial robots. In the study, first, the motion-coupling characteristics of cable-driven joints and motion-decoupling methods based on translational and rotational compensation were examined. Next, the mechanical structure of the CDSSR was designed, including motion-decoupling mechanisms, cable-driven differential wrists, and tension-amplification mechanisms. In addition, an improved non-singular inverse kinematics approach incorporating dual-arm angles and configuration control parameters was developed. Finally, an experimentally scaled prototype of the proposed robot was constructed, and motion decoupling and spray trajectory planning experiments were conducted. The experimental and simulation results demonstrate the effectiveness of the non-singular inverse kinematics method in achieving efficient inverse kinematics solutions under global configuration control. Furthermore, the motion decoupling mechanisms designed for the serial robot successfully accomplished motion decoupling.

An inverse kinematic method for non-spherical wrist 6DOF robot based on reconfigured objective function

An inverse kinematic method for non-spherical wrist 6DOF robot based on reconfigured objective function

Shape-controllable inverse kinematics of hyper-redundant robots based on the improved FABRIK method

AbstractHyper-redundant robots have good prospects for applications in confined space due to their high flexibility and slim body size. However, the super-redundant structure brings great challenges for its inverse kinematics with shape constraints. Unfortunately, traditional Jacobian pseudo-inverse-based inverse kinematics method and forward and backward reaching inverse kinematics (FABRIK) method are difficult to constrain the arm shape and realize trajectory tracking in confined spaces. To solve this problem, we propose a shape-controllable FABRIK method to satisfy the given path and shape constraints. Firstly, the kinematic model of the hyper-redundant robot is established, and the canonical FABRIK method is introduced. Based on the preliminary works, the single-layer improved FABRIK method is developed to solve the position and pointing inverse kinematics considering path environment and joint angle constraints instead of two-layer geometric iterations. For tracking the desired end roll angles, the polygonal virtual arm is designed. The real arm roll angle is achieved by controlling its winding on the virtual arm. In this way, the shape can be controlled. Finally, we compare the proposed method with other three approaches by simulations. Results show that the proposed method is more efficient and the arm shape is controllable.

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.

An analytical approach based on Dixon resultant for the inverse kinematics of 6R robot manipulators with offset wrists

6-revolute (6R) robot manipulators with offset wrists are widely applied in industrial scenarios. However, the autonomous and highly-precise manipulations of these robots are restricted for online industrial uses due to the lack of effective inverse kinematic methods. The inverse kinematic problem for 6R robot manipulators with offset wrists is addressed with a novel kinematic modelling and elimination approach in this study. To begin, kinematic models with non-redundant equations for joint variables are established An improved Dixon elimination approach is then introduced for inverse kinematic calculation to reduce the high computational cost and get rid of the singularity issues. The core is to efficiently extract the linear terms from variable sequences, such that the number of terms can be reduced in the polynomial equations. By further examining the characteristics of offset wrists, the fourth and fifth joint variables are eliminated from kinematic formulas, without increasing the polynomial degrees. The formulas are demonstrated to produce a polynomial with a single joint variable and a minimum degree using the elimination approach. Finally, experiments are carried out to verify the computing performance of the inverse kinematic problem. The main focus of this study is to develop a systematic and automatic procedure for solving the inverse kinematic problem for 6R robot manipulators with offset wrists and producing highly precise and efficient solutions by means of a novel modelling and elimination method.

Inverse kinematics and multi-objective configuration optimization of the SSRMS manipulator

The Space Station Remote Manipulator System (SSRMS) type redundant manipulator with higher flexibility and foldability is widely used in the space environment. Inverse kinematics and multi-objective configuration optimization are analyzed in this paper. An arm angle parameterized inverse kinematics method using the approximate solution and error compensation scheme is proposed, which has the advantages of not requiring a selection of initial estimates of joint variables, being insensitive to Jacobian matrix singularities, having no pose error, and finding multiple solutions. In addition, Multiple Objective Particle Swarm Optimization (MOPSO) scheme is adopted to optimize the arm angle trajectory in null space, and the optimization index is set as joint torque and manipulability. Unlike traditional trajectory planning methods, we synthesize null space and configuration control to provide a novel perspective for trajectory planning. Finally, the experiments prove that the inverse kinematics algorithm is efficient and reliable, and the effectiveness of the configuration optimization method is verified by the numerical simulation of single objective and multi-objective optimization.