Kinematic Performance Research Articles

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.

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.

Mission Planning and Trajectory Optimization in UAV Swarm for Track Deception against Radar Network

In this article, a mission planning and trajectory optimization scheme in unmanned aerial vehicle (UAV) swarm for track deception against radar networks is proposed. The core of this scheme is to formulate the track deception problem as a model with the objective of simultaneously maximizing the number of phantom tracks while minimizing the total flight distance of the UAV swarm, subject to the constraints of UAV kinematic performance, phantom track rotation angles, and a homology test. It is shown that the formulated track deception problem is a mixed-integer programming, multivariable, and non-linear optimization model. By incorporating mission planning based on platform reuse and a particle swarm optimization (PSO) algorithm, a three-stage solution methodology is proposed to tackle the above problem. Through joint optimization for mission planning and flight trajectories of the UAV swarm, a low-speed UAV swarm is capable of generating a number of high-speed phantom tracks. Numerical results demonstrate that the proposed scheme enables a low-speed UAV swarm to generate as many high-speed phantom tracks as possible, effectively achieving track deception against radar network.

Power absorption and flow-field characteristics analysis for oscillating coaxial twin-buoy wave energy converter by using CFD

The energy conversion capacity of wave energy conversion devices highly depends on the hydrodynamic characteristics of the energy-harvesting structure. To investigate the effect of hydrodynamic performance on the power conversion characteristics, a twin-buoy wave energy converter (WEC) was investigated by using a three-dimensional numerical wave pool based on the Computational Fluid Dynamics (CFD) method. Several factors are examined, including the elasticity coefficient of the anchor chain, the bottom configuration of the floating body, and the power take-off (PTO) damping coefficient. The heave displacement, heave velocity, and heave force of the converter are calculated under specific wave parameters, and the flow field cloud diagram during the heave motion is analyzed. The results indicate that a wave energy converter with a hemispherical floating body exhibits the best kinematic performance. The influence of the mechanical damping coefficient on the energy conversion performance of the device is studied. By appropriately reducing the mechanical damping coefficient, the energy capturing capability of the device can be increased to a certain extent. These findings can serve as a theoretical basis for the application of deep-water wave energy conversion in engineering and the optimization of future WEC designs.

Design and Analysis of a Robotic Gripper Mechanism for Fruit Picking

A gripper is the critical component of the robot end effector for the automatic harvesting of fruit, which determines whether the fruit can be harvested intact or undamaged. In this paper, a robotic gripper mechanism based on three-finger and variable-angle design is designed and analyzed for spherical or cylindrical fruit picking. Among the three fingers of the mechanical gripper, two fingers are rotatable through a pair of synchronous gears to ensure enough contact area for the grasping surfaces, which adapt to fruits of different sizes, such as cherry, loquat, zucchini, and so on. Furthermore, the mathematical relationship between gripper driving force and finger gripping force is obtained by the kinematic analysis of the gripper to realize stable grasping, and a grasping index is employed for the structural parameter optimization of our gripper. The grasping motion is analyzed, and the kinematic simulations are carried out, when the driving speeds of the gripper are 5 mm/s, 10 mm/s, and 15 mm/s, respectively. The system transfer function related to driving speed is obtained by curve fitting. Then, the grasping experiments are conducted with various spherical and cylindrical fruit, of which the weights are between 8 and 300 g and the diameters are from 9 to 122 mm. The experimental results demonstrate that our gripper has good kinematic performance and fruit adaptability. At the same time, the grasping is stable and reliable while no obvious damage appears on the fruit surface.

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

Kinematic performance evaluation method of a 3-DOF redundantly actuated parallel manipulator

Kinematic performance evaluation method of a 3-DOF redundantly actuated parallel manipulator

Organization of conceptual tool knowledge following left and right brain lesions: Evidence from neuropsychological dissociations and multivariate disconnectome symptom mapping

The aim of this work was to better understand the organization of conceptual tool knowledge following stroke. We explored specifically the link between manipulation kinematics and manipulation hand posture; and the link between manipulation kinematics and function relations in left brain-damaged (n = 30) and right brain-damaged (n = 30) patients. We examined the performance of brain-damaged patients in conceptual tool tasks using neuropsychological dissociations and disconnectome symptom mapping. Our results suggest that manipulation kinematics is more impaired than function relations, following left or right brain lesions. We also observed that manipulation kinematics and manipulation hand posture are dissociable dimensions but are still highly interrelated, particularly in left brain-damaged patients. We also found that the corpus callosum and bilateral superior longitudinal fasciculus are involved in action and semantic tool knowledge following left brain lesions. Our results provide evidence that the right hemisphere contains conceptual tool representations. Further studies are needed to better understand the mechanisms supporting the cognitive recovery of conceptual tool knowledge. An emerging hypothesis is that the right hemisphere may support functional recovery through interhemispheric transfer following a left hemisphere stroke.