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We present a derivation from the first principles of the coupled equations of motion of an active self-diffusiophoretic Janus motor and the hydrodynamic densities of its fluid environment that are nonlinearly displaced from equilibrium. The derivation makes use of time-dependent projection operator techniques defined in terms of slowly varying coarse-grained microscopic densities of the fluid species number, total momentum, and energy. The exact equations of motion are simplified using time scale arguments, resulting in Markovian equations for the Janus motor linear and angular velocities with average forces and torques that depend on the fluid densities. For a large colloid, the fluid equations are separated into bulk and interfacial contributions, and the conditions under which the dynamics of the fluid densities can be accurately represented by bulk hydrodynamic equations subject to boundary conditions on the colloid are determined. We show how the results for boundary conditions based on continuum theory can be obtained from the molecular description and provide Green–Kubo expressions for all transport coefficients, including the diffusiophoretic coupling and the slip coefficient. [ABSTRACT FROM AUTHOR]

In this paper, a one-level operator splitting method (OOSM) and a two-level operator splitting method (TOSM) for the two-dimensional or three-dimensional (2D/3D) unsteady incompressible micropolar fluid equations with double diffusion convection (IMFDDC) are proposed and analyzed. Firstly, a OOSM is constructed, which consists of five steps. The projection strategy is adopted to get the values of linear velocity and pressure in the first two steps, then the three elliptic subproblems about the angular velocity, the temperature, and the concentration variables are solved in the last three steps. The original variables with the predefined boundary conditions need to be solved separately in each step. Next, in order to solve the problem efficiently, a TOSM is presented, which only solves the nonlinear equations in the coarse level subspaces and the Oseen type linearized equations in the fine level. The numerical analysis of stability and error estimates of the fully discrete methods show that TOSM can reach the same accuracy as the OOSM with H ∼ O (h 2 / 3). Numerical examples are provided to confirm the effectiveness and reliability of the proposed methods. [ABSTRACT FROM AUTHOR]

Electromagnetic plasma propulsion is generated by the linear plasma propulsion (LPP) apparatus. The LPP device is upgraded to operate and simulate at a maximum energy of 5.4 kJ. The cathode's cylindrical upper portion is changed into a hemispherical shape as part of the upgrading process to boost the current sheath (CS) acceleration. According to the model, the CS moves in the z-direction with a linear velocity while moving in the θ-direction with an angular velocity. When the plasma is squeezed and compressed, it is driven through the extension tube. The model describes the CS motion, its characteristics, and the propelled plasma using four phases: an axial, an angular radial, a reflected, and an expansion phases. The simulated Ith and experimental Iex current signals were compared to prove the validity of the model assumption, where the values of Ith and Iex were 89.7 and 88 kA, respectively. According to the results, as the motion angle increases in the angular radial phase, the CS compresses, elongates, and is forced into the extension tube. The results showed that the peaks of both plasma inductance, velocity, temperature, and propelled plasma length were 36.3 nH, 6.36 cm/μs, 6.72 eV, and 3.22 cm, respectively. [ABSTRACT FROM AUTHOR]

The development and study of an optimal control method for the problem of controlling the formation of a group of mobile robots is still a current and popular theme of work. However, there are few works that take into account the issues of time synchronization of units in a decentralized group. The motivation for taking up this topic was the possibility of improving the accuracy of the movement of a group of robots by including dynamic time synchronization in the control algorithm. The aim of this work was to develop a two-layer synchronous motion control system for a decentralized group of mobile robots. The system consists of a master layer and a sublayer. The sublayer of the control system performs the task of tracking the reference trajectory using a single robot with a kinematic and dynamic controller. In this layer, the input and output signals are linear and angular velocity. The master layer realizes the maintenance of the desired group formation and synchronization of robots during movement. Consensus tracking and virtual structure algorithms were used to implement this level of control. To verify the correctness of operation and evaluate the quality of control for the proposed proprietary approach, simulation studies were conducted in the MATLAB/Simulink environment, followed by laboratory tests using real robots under ROS. The developed system can successfully find application in transportation and logistics tasks in both civilian and military areas. [ABSTRACT FROM AUTHOR]

The maximum linear (or translational) velocity achievable by an omnidirectional platform is not uniform as it depends on the angular orientation of the motion. This velocity is limited by the maximum angular velocity of the motors driving the wheels and also depends on the mechanical configuration and orientation of the wheels. This paper proposes a procedure to compute an upper bound for the translational velocity, named the consistent velocity of the omnidirectional platform, which is defined as the minimum of the maximum translational velocities achievable by the platform in any angular orientation with no wheel slippage. The consistent velocity is then a uniform translational velocity always achievable by the omnidirectional platform regardless of the angular orientation of the motion. This paper reports the consistent velocity for a set of omnidirectional platforms with three omni wheels that have the same radius and angular distribution but different angular orientations. Results have shown that these platforms can achieve different maximum velocities in different angular orientations although the consistent velocity is the same for all of them. Results have also shown that the consistent velocity has a linear relation with the angular velocity of the motion. The consistent velocity of a mobile platform can be used by its path-planning algorithm as an upper bound that guarantees the execution of any omnidirectional motion at a uniform and maximum translational velocity. [ABSTRACT FROM AUTHOR]

We investigate a fully discrete modular grad-div (MGD) stabilization algorithm for solving the incompressible micropolar Navier-Stokes equations (IMNSE) model, which couples the incompressible Navier-Stokes equations and the angular momentum equation together. The mixed finite element (FE) method is applied for the spatial discretization. The time discretization is based on the BDF2 implicit scheme for the linear terms and the two-step linearly extrapolated scheme for the convective terms. The considered algorithm constitutes two steps, which involve a post-processing step for linear velocity. First, we decouple the fully coupled IMNSE model into two smaller subphysics problems at each time step (one is for the linear velocity and pressure, the other is for the angular velocity), which reduces the size of the linear systems to be solved and allows for parallel computing of the two sub-physics problems. Then, in the post-processing step, we only need to solve a symmetrical positive determined grad-div system of linear velocity at each time step, which does not increase the computational complexity by much. However, the post-processing step can improve the solution quality of linear velocity. Moreover, we obtain unconditional stability, and error estimates of the linear velocity and angular velocity. Finally, several numerical experiments involving threedimensional and two-dimensional settings are used to validate the theoretical findings and demonstrate the benefits of the modular grad-div (MGD) stabilization algorithm. [ABSTRACT FROM AUTHOR]

This study explores positioning and obstacle avoidance control for autonomous surface vehicles (ASVs) by considering equivalent elliptical-shaped obstacles. Firstly, compared to most Barrier Lyapunov function (BLF) methods that approximate obstacles as circles, a novel BLF is improved by introducing an elliptical obstacle model. This improvement uses ellipses instead of traditional circles to equivalent obstacles, effectively resolving the issue of excessive conservatism caused by over-expanded areas during the obstacle equivalence process. Secondly, unlike traditional obstacle avoidance approaches based on BLF, to achieve constraint control of angle and angular velocity, a method based on model predictive control (MPC) is introduced to optimize local angle planning. By incorporating angular error constraints, this ensures that the directional error of the ASV remains within a restricted range. Furthermore, an auxiliary function of directional error is introduced into the ASV's linear velocity, ensuring that the ASV parks and adjusts its direction when the deviation in angle becomes too large. This innovation guarantees the linearization of the ASV system, addressing the complexity of traditional MPC methods when dealing with nonlinear second-order ASV systems. Ultimately, the efficacy of our proposed approach is validated through rigorous experimental simulations conducted on the MATLAB platform. [ABSTRACT FROM AUTHOR]

Autonomous mobile robots are essential to the industry, and human–robot interactions are becoming more common nowadays. These interactions require that the robots navigate scenarios with static and dynamic obstacles in a safely manner, avoiding collisions. This paper presents a physical implementation of a method for dynamic obstacle avoidance using a long short-term memory (LSTM) neural network that obtains information from the mobile robot's LiDAR for it to be capable of navigating through scenarios with static and dynamic obstacles while avoiding collisions and reaching its goal. The model is implemented using a TurtleBot3 mobile robot within an OptiTrack motion capture (MoCap) system for obtaining its position at any given time. The user operates the robot through these scenarios, recording its LiDAR readings, target point, position inside the MoCap system, and its linear and angular velocities, all of which serve as the input for the LSTM network. The model is trained on data from multiple user-operated trajectories across five different scenarios, outputting the linear and angular velocities for the mobile robot. Physical experiments prove that the model is successful in allowing the mobile robot to reach the target point in each scenario while avoiding the dynamic obstacle, with a validation accuracy of 98.02%. [ABSTRACT FROM AUTHOR]

Autonomous navigation and information gathering in challenging environments are demanding since the robot's sensors may be susceptible to non-negligible noise, its localization and mapping may be subject to significant uncertainty and drift, and performing collision-checking or evaluating utility functions using a map often requires high computational costs. We propose a learning-based method to efficiently tackle this problem without relying on a map of the environment or the robot's position. Our method utilizes a Collision Prediction Network (CPN) for predicting the collision scores of a set of action sequences, and an Information gain Prediction Network (IPN) for estimating their associated information gain. Both networks assume access to a) the depth image (CPN) or the depth image and the detection mask from any visual method (IPN), b) the robot's partial state (including its linear velocities, z -axis angular velocity, and roll/pitch angles), and c) a library of action sequences. Specifically, the CPN accounts for the estimation uncertainty of the robot's partial state and the neural network's epistemic uncertainty by using the Unscented Transform and an ensemble of neural networks. The outputs of the networks are combined with a goal vector to identify the next-best-action sequence. Simulation studies demonstrate the method's robustness against noisy robot velocity estimates and depth images, alongside its advantages compared to state-of-the-art methods and baselines in (visually-attentive) navigation tasks. Lastly, multiple real-world experiments are presented, including safe flights at 2.5 m/s in a cluttered corridor, and missions inside a dense forest alongside visually-attentive navigation in industrial and university buildings. [ABSTRACT FROM AUTHOR]

This paper presents a study on optimal design to determine the installation position and link lengths of a robot within a designated workspace for welding, aiming to minimize singularities during the robot's motion. Bi-objective functions are formulated to minimize singularities while maximizing the volumes of linear velocity manipulability ellipsoid and angular velocity manipulability ellipsoid, respectively, ensuring isotropy. We have constructed a simulation environment incorporating PID control to account for robot tracking errors. This environment was utilized as a simulator to derive a Bi-objective function set within a genetic algorithm. Through this, we optimized four robot link length variables and two installation position variables, selecting the optimal design variables on the Pareto Front. In the standard work object, the volume average of the linear velocity manipulability ellipsoid was confirmed to have improved by 72% compared to the initial level, and the isotropy of the angular velocity manipulability ellipsoid was confirmed to have improved by 23% compared to the initial level. Furthermore, correlation analysis between design parameters identified those with a high correlation with the objective functions, and the analysis results are discussed. [ABSTRACT FROM AUTHOR]

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Fast‐start predator‐escape performance and its sensitivity to temperature (24, 30, and 36°C) were evaluated in mummichog Fundulus heteroclitus across a range of body sizes spanning YOY to adult (35–68 mm standard length). Mummichogs exhibit isometry of body dimensions and areas of the dorsal and anal fins but negative allometry of the caudal fin area. These scaling relationships are consistent with observed decreases in fast‐start angular velocities with increasing body size. Linear velocity, on the contrary, does not vary with size, and both large and small mummichogs are capable of traversing similar distances in a given amount of time. In addition, temperature influences fast‐start performance in similar ways over the size range, though the magnitude of the effect varies with size for some performance measures. In general, fast‐start performance increases with test temperature, but mummichogs acclimated to warmer temperatures exhibit lower performance at each test temperature. Altogether, our results suggest that mummichogs across the adult size range may suffer decreases in their predator‐escape performance as increasing sea temperatures combine with short‐term temperature fluctuations in the estuaries these fish occupy. [ABSTRACT FROM AUTHOR]

We consider a PDE-ODE model of a flexible satellite that is composed of two identical flexible solar panels and a center rigid body. We prove that the satellite model is exponentially stable in the sense that the energy of the solutions decays to zero exponentially. In addition, we construct two internal model based controllers, a passive controller and an observer based controller, such that the linear and angular velocities of the center rigid body converge to the given sinusoidal signals asymptotically. A numerical simulation is presented to compare the performances of the two controllers. [ABSTRACT FROM AUTHOR]

This paper addresses the trajectory tracking control problem of a quadrotor under uncertain model parameters, external disturbances, and unmeasurable linear velocity. The main contribution of this paper is to present a geometric control strategy with a simple structure and easily adjustable parameters, which combines the differentiator and uncertainty and disturbance estimator techniques to achieve global trajectory tracking control. First, a cascade control framework is introduced to solve the strong coupling and under actuated problems of quadrotors. Furthermore, an anti disturbance outer-loop differentiator-based position controller is designed based on the uncertainty and disturbance estimators (UDE) to achieve accurate quadrotor tracking of the desired trajectory. The higher order control inputs of the translational dynamics are estimated using a differentiator to determine the desired angular velocity and its derivative. Then, a robust inner-loop geometric controller is derived in Lie algebraic space using the rotation matrix. After that, the stability analysis of the closed-loop system is executed using the Lyapunov stability theory. Finally, the numerical simulation verifies that the method enables the quadrotor to have strong robustness and excellent tracking capability in the presence of large initial angles, time-varying disturbances, and unmeasured linear velocity. [ABSTRACT FROM AUTHOR]

Aiming at the cumbersome feature extraction steps and poor real-time performance of traditional visual servoing algorithms, an end-to-end direct visual servoing algorithm based on convolutional neural network is proposed. By directly predicting the instantaneous linear velocity and instantaneous angular velocity of the camera installed at the end of the robotic arm, servo positioning works without the need to label handcrafted features, camera intrinsics, or depth information. Firstly, the image observed by the camera is input into the GhostNet feature extraction network for information extraction, and the bottleneck attention module (BAM) is integrated into the network to enhance the spatial information and channel information of the target object. Then, the fully connected layer is used as the speed regression function, the linear velocity and angular velocity are decoupled and regressed. Finally, a real-time capture method is used to create the dataset required for training in the real environment, and the velocity labels are generated according to the position-based visual servo control law algorithm. Efficient and accurate localization and tracking tasks are accomplished under the trained initial pose. The experimental test results in a large number of real scenes verify the effectiveness of the algorithm, and it is also robust to scene background information. [ABSTRACT FROM AUTHOR]

Differential drive mobile robots, being widely used in several industrial and domestic applications, are increasingly demanding when concerning precision and satisfactory maneuverability. In the present paper, the problem of independently controlling the velocity and orientation angle of a differential drive mobile robot is investigated by developing an appropriate two stage nonlinear controller embedded on board and also by using the measurements of the speed and accelerator of the two wheels, as well as taking remote measurements of the orientation angle and its rate. The model of the system is presented in a nonlinear state space form that includes unknown additive terms arising from external disturbances and actuator faults. Based on the nonlinear model of the system, the respective I/O relation is derived, and a two-stage nonlinear measurable output feedback controller, analyzed into an internal and an external controller, is designed. The internal controller aims to produce a decoupled inner closed-loop system of linear form, regulating the linear velocity and angular velocity of the mobile robot independently. The internal controller is of the nonlinear PD type and uses real time measurements of the angular velocities of the active wheels of the vehicle, as well as the respective accelerations. The external controller aims toward the regulation of the orientation angle of the vehicle. It is of a linear, delayed PD feedback form, offering feedback from the remote measurements of the orientation angle and angular velocity of the vehicle, which are transmitted to the controller through a wireless network. Analytic formulae are derived for the parameters of the external controller to ensure the stability of the closed-loop system, even in the presence of the wireless transmission delays, as well as asymptotic command following for the orientation angle. To compensate for measurement noise, external disturbances, and actuator faults, a metaheuristic algorithm is proposed to evaluate the remaining free controller parameters. The performance of the proposed control scheme is evaluated through a series of computational experiments, demonstrating satisfactory behavior. [ABSTRACT FROM AUTHOR]

Objective: To explore the inherent relationship between lower limb biomechanical indicators and effective scoring values of double roundhouse kick (DRK) by taekwondo athletes, and to find key biomechanical factors that trigger effective scoring. Methods: Using the DAEDO Protector and Scoring System (PSS) in conjunction with the Vicon optical motion capture system and Kistler 3D force plate, kinematic and dynamic indicators of the front kicking motion were obtained from 12 professional taekwondo athletes (18.00 ± 2.20 years, 182.15 ± 8.62 cm and 70.00 ± 14.82 kg). The correlation between kinematics, dynamics, and scoring values was initially analyzed using bivariate linear correlation. Subsequently, based on the results of the linear correlation analysis, a stepwise regression analysis was performed to establish a stepwise regression equation. Results: The results reveal that during the First Hit, there is a significant positive correlation (r > 0, p < 0.05) between peak hip flexion angular velocity of the dominant leg, knee abduction angle, and peak foot horizontal plane linear velocity of the non-dominant leg with effective score. On the other hand, peak ankle flexion angular velocity of the non-dominant leg, peak foot sagittal plane linear velocity, peak hip abduction angle, and peak hip flexion angle of the dominant leg exhibit a significant negative correlation (r < 0, p < 0.05) with effective score. These correlations hold statistical significance (DW> 1.023). During the Second Hit, there is a significant positive correlation (r > 0, p < 0.05) between peak ankle internal rotation angular velocity of the dominant leg, foot coronal plane linear velocity, hip adduction angular velocity, and peak ankle internal rotation moment of the non-dominant leg with effective score. Conversely, peak hip flexion angle of the dominant leg shows a significant negative correlation (r < 0, p < 0.05) with effective score. All these variables have a statistically significant impact on effective score (DW > 1.023). Conclusion: Explosive power, body posture, adequate terminal velocity, and body rotation have an association with effective scoring of the electronic protector. The peak angular velocity of the ankle joint of the dominant leg and the peak linear velocity of the foot horizontal plane of the non-dominant leg significantly contribute to the effectiveness score of the electronic protector. [ABSTRACT FROM AUTHOR]

This study introduces a framework to improve upper extremity motion-based telemanipulation by component-wise rescaling (CWR) of spatial twist. This method allows for separate adjustments of linear and angular scaling parameters, significantly improving precision and dexterity even when the operator's heading direction changes. By finely controlling both the linear and angular velocities independently, the CWR method enables more accurate telemanipulation in tasks requiring diverse speed and accuracy based on personal preferences or task-specific demands. The study conducted experiments confirming that operators could precisely control the robot gripper with a steady, controlled motion even in confined spaces, irrespective of changes in the subject's body-heading direction. The performance evaluation of the proposed motion-scaling-based telemanipulation leveraged Optitrack's motion-capture system, comparing the trajectories of the operator's hand and the manipulator's end effector (EEF). This verification process solidified the efficacy of the developed framework in enhancing telemanipulation performance. [ABSTRACT FROM AUTHOR]

Robot workpiece machining is interesting in industry as it offers some advantages, such as higher flexibility in comparison with the conventional approach based on CNC technology. However, in recent years, we have been facing a strong progressive shift to custom-based manufacturing and low-volume/high-mix production, which require a novel approach to automation via the employment of collaborative robotics. However, collaborative robots feature only limited motion capability to provide safety in cooperation with human workers. Thus, it is highly necessary to perform more detailed robot task planning to ensure its feasibility and optimal performance. In this paper, we deal with the problem of studying kinematic robot performance in the case of such manufacturing tasks, where the robot tool is constrained to follow the machining path embedded on the workpiece surface at a prescribed orientation. The presented approach is based on the well-known concept of manipulability, although the latter suffers from physical inconsistency due to mixing different units of linear and angular velocity in a general 6 DOF task case. Therefore, we introduce the workpiece surface constraint in the robot kinematic analysis, which enables an evaluation of its available velocity capability in a reduced dimension space. Such constrained robot kinematics transform the robot's task space to a two-dimensional surface tangent plane, and the manipulability analysis may be limited to the space of linear velocity only. Thus, the problem of physical inconsistency is avoided effectively. We show the theoretical derivation of the proposed method, which was verified by numerical experiments. [ABSTRACT FROM AUTHOR]

The current paper concerned with a non-linear convection flow of the Oldroyd-B nanofluid at a point of stagnation across a rotating sphere under the influence of convective heat and passive control conditions. The analysis of energy and concentration transition has been scrutinized based on the Cattaneo–Christov diffusion model. The formulated coupled mathematical problem involving boundary requirements can be alerted to a set of highly nonlinear ordinary differential equations by employing similarity analysis. The numerical solution for the governing problem was computed by utilizing bvp4c solver method. The performance of velocity fields, skin friction drag, energy, heat transfer rate, and concentration for various control parameters has been analyzed using diagrams and tables. The findings stipulated that velocity, temperature, and nanoparticle are enhanced for the relaxation time constant while they decay for the retardation time parameter. The upshots also confirmed that enlarging magnetic parameters leads to improve both linear velocity and coefficient of skin friction. The velocity profiles are enhanced as a function of the rotation constant. But, normal velocity declines for buoyancy force ratio, and the same trend is being noted for magnetic and relaxation time parameters on angular velocity. The fluid temperature declines for the Prandtl number and augments for thermal convective parameter. The coefficient of skin friction decreases for larger thermal relaxation and rotation parameters, whereas an analogous effect is being noticed for Brownian parameter on the concentration field. Further, the thermophoresis parameter displays an enhancing tendency on temperature as well as concentration profile while bringing down the Nusselt number. The Lewis number and solutal relaxation parameter filter the concentration field. The graph of the streamline is sketched for identical values of the magnetic parameter and noticed that the contour lines increased as magnified. Confirmation of the current outcomes with former studies is presented. [ABSTRACT FROM AUTHOR]

Sea ice profoundly influences the polar environment and the global climate. Traditionally, sea ice has been modeled as a continuum under Eulerian coordinates to describe its largescale features, using, for instance, viscous-plastic rheology. Recently, Lagrangian particle models, also known as the discrete element method models, have been utilized for characterizing the motion of individual sea ice fragments (called floes) at scales of 10 km and smaller, especially in marginal ice zones. This paper develops a multiscale model that couples the particle and the continuum systems to facilitate an effective representation of the dynamical and statistical features of sea ice across different scales. The multiscale model exploits a Boltzmann-type system that links the particle movement with the continuum equations. For the small-scale dynamics, it describes the motion of each sea ice floe. Then, as the large-scale continuum component, it treats the statistical moments of mass density and linear and angular velocities. The evolution of these statistics affects the motion of individual floes, which in turn provides bulk feedback that adjusts the large-scale dynamics. Notably, the particle model characterizing the sea ice floes is localized and fully parallelized in a framework that is sometimes called superparameterization, which significantly improves computational efficiency. Numerical examples demonstrate the effective performance of the multiscale model. Additionally, the study demonstrates that the multiscale model has a linear-order approximation to the truth model. [ABSTRACT FROM AUTHOR]

This Airships are lighter than air vehicles and due to their growing number of applications, they are becoming attractive for the research community. Most of the applications require an airship autonomous flight controller which needs an accurate model and state information. Usually, airship states are affected by noise and states information can be lost in the case of sensor's faults, while airship model is affected by model inaccuracies and model uncertainties. This paper presents the application of nonlinear and Bayesian estimators for estimating the states and model uncertainties of neutrally buoyant airship. It is considered that minimum sensor measurements are available, and data is corrupted with process and measurement noise. A novel lumped model uncertainty estimation approach is formulated where airship model is augmented with six extra state variables capturing the model uncertainty of the airship. The designed estimator estimates the airship model uncertainty along with its states. Nonlinear estimators, Extended Kalman Filter and Unscented Kalman Filter are designed for estimating airship attitude, linear velocities, angular velocities and model uncertainties. While Particle filter is designed for the estimation of airship attitude, linear velocities and angular velocities. Simulations have been performed using nonlinear 6-DOF simulation model of experimental airship for assessing the estimator performances. 1 - σ uncertainty bound and error analysis have been performed for the validation. A comparative study of the estimator's performances is also carried out. [ABSTRACT FROM AUTHOR]

The sense of orientation of an animal is derived from the head direction (HD) system found in several limbic structures and depends on an intact vestibular labyrinth. However, how the vestibular system influences the generation and updating of the HD signal remains poorly understood. Anatomical and lesion studies point toward three key brainstem nuclei as key components for generating the HD signal--nucleus prepositus hypoglossi, supragenual nucleus, and dorsal paragigantocellularis reticular nuclei. Collectively, these nuclei are situated between the vestibular nuclei and the dorsal tegmental and lateral mammillary nuclei, which are thought to serve as the origin of the HD signal. To determine the types of information these brain areas convey to the HD network, we recorded neurons from these regions while female rats actively foraged in a cylindrical enclosure or were restrained and rotated passively. During foraging, a large subset of cells in all three nuclei exhibited activity that correlated with the angular head velocity (AHV) of the rat. Two fundamental types of AHV cells were observed; (1) symmetrical AHV cells increased or decreased their firing with increases in AHV regardless of the direction of rotation, and (2) asymmetrical AHV cells responded differentially to clockwise and counterclockwise head rotations. When rats were passively rotated, some AHV cells remained sensitive to AHV, whereas firing was attenuated in other cells. In addition, a large number of AHV cells were modulated by linear head velocity. These results indicate the types of information conveyed from the vestibular nuclei that are responsible for generating the HD signal. [ABSTRACT FROM AUTHOR]

A three-dimensional reachable set for a nonlinear controlled object "Dubins car" is investigated. The control is the angular velocity of rotation of the linear velocity vector. An integral quadratic constraint is imposed on the control. Based on the Pontryagin maximum principle, a description of the motions generating the boundary of the reachable set is given. The motions leading to the boundary are optimal Euler elasticae. Simulation results are presented. [ABSTRACT FROM AUTHOR]

The Orthoptera are a diverse insect order well known for their locomotive capabilities. To jump, the bush-cricket uses a muscle actuated (MA) system in which leg extension is actuated by contraction of the femoral muscles of the hind legs. In comparison, the locust uses a latch mediated spring actuated (LaMSA) system, in which leg extension is actuated by the recoil of spring-like structure in the femur. The aim of this study was to describe the jumping kinematics of Mecopoda elongata (Tettigoniidae) and compare this to existing data in Schistocerca gregaria (Acrididae), to determine differences in control of rotation during take-off between similarly sized MA and LaMSA jumpers. 269 jumps from 67 individuals of M. elongata with masses from 0.014 g to 3.01 g were recorded with a high-speed camera setup. In M. elongata, linear velocity increased with mass0.18 and the angular velocity (pitch) decreased with mass−0.13. In S. gregaria, linear velocity is constant and angular velocity decreases with mass−0.24. Despite these differences in velocity scaling, the ratio of translational kinetic energy to rotational kinetic energy was similar for both species. On average, the energy distribution of M. elongata was distributed 98.8% to translational kinetic energy and 1.2% to rotational kinetic energy, whilst in S. gregaria it is 98.7% and 1.3%, respectively. This energy distribution was independent of size for both species. Despite having two different jump actuation mechanisms, the ratio of translational and rotational kinetic energy formed during take-off is fixed across these distantly related orthopterans. [ABSTRACT FROM AUTHOR]

This paper presents an approach for designing angular and linear velocity observers for rigid bodies using two inertial vectors and one landmark measurements directly. Compared with the classical velocity estimation algorithms, the proposed observer does not need to reconstruct the pose information from measurements nor be coupled with velocity sensors. The linear‐time varying dynamics of the estimation error equation are analyzed, rigorously showing the uniform local exponential stability of the observer. Simulations are conducted to illustrate the significant performance of the proposed method. [ABSTRACT FROM AUTHOR]

To solve the problems of backstepping error and poor dynamic tracking approach rate in traditional PID neural network control in UAV formation flight control, a Leader-Follower UAV formation flight control method based on feature modelling is proposed,and the pose relationship model between virtual follower and pilot is established by trajectory tracking and pose dynamic fitting. The pose distribution of thefollower is analyzed in the ground coordinate system, and the parameter information of linear velocity and angular velocity control of UAV is obtained, and the backstepping sliding mode formation controller is formed. The variable structure PID neural network controller is used to design the flight control law of UAV formation, and the fast piecewise power approaching factor is introduced into the PID controller to eliminate the chattering of sliding mode control. The simulation results show that this method can ensure the rapidity of UAV formation flight control also show strong anti-jamming ability. Due to the fast piecewise power approach rate, the UAVs can complete the UAV formation reorganization under disturbance and buffeting in a short time, and the trajectory tracking error approaches zero, and it has good anti-buffeting ability. [ABSTRACT FROM AUTHOR]

A UUV can perform tasks such as underwater surveillance, reconnaissance, surveillance, and tracking by being equipped with sensors and different task modules. Due to the complex underwater environment, the UUV must have good collision avoidance planning algorithms to avoid various underwater obstacles when performing tasks. The existing path planning algorithms take a long time to plan and have poor adaptability to the environment. Some collision-avoidance planning algorithms do not take into account the kinematic limitations of the UUV, thus placing high demands on the performance and control algorithms of UUV. This article proposes a PPO−DWA collision avoidance planning algorithm for the UUV under static unknown obstacles, which is based on the proximal policy optimization (PPO) algorithm and the dynamic window approach (DWA). This algorithm acquires the obstacle information from forward-looking sonar as input and outputs the corresponding continuous actions. The PPO−DWA collision avoidance planning algorithm consists of the PPO algorithm and the modified DWA. The PPO collision avoidance planning algorithm is only responsible for outputting the continuous angular velocity, aiming to reduce the difficulty of training neural networks. The modified DWA acquires obstacle information and the optimal angular velocity from the PPO algorithm as input, and outputs of the linear velocity. The collision avoidance actions output by this algorithm meet the kinematic constraints of UUV, and the algorithm execution time is relatively short. The experimental data demonstrates that the PPO−DWA algorithm can effectively plan smooth collision-free paths in complex obstacle environments, and the execution time of the algorithm is acceptable. [ABSTRACT FROM AUTHOR]

This paper presents a novel iterative algorithm incorporated in a user-friendly GUI for modeling the kinematics of multiple looped N-bar closed-loop mechanisms. Past research works have used custom coding or expensive commercial software to analyze the mechanisms of specific applications. The proposed algorithm focuses on kinematics and offers a quick, easy-to-use, cost-effective solution to analyze a wide range of generic mechanisms, reducing the need for custom coding and lowering computational costs. The algorithm employs algebraic equations, such as solving complex closed-loop vector equations using the Euler form of complex numbers, to simulate and derive the unknowns necessary to characterise any generic closed-loop mechanism. The Python code implemented in the algorithm adapts to various scenarios by utilising available information on the position, velocity, and acceleration variables of the mechanisms. The simulation tool can display real-time color contour plots (RGB color scale) for linear and angular velocities and accelerations, simulate mechanisms with multiple loops and switch configurations, and find inverse mechanisms. The approach for solving multiple loop problems and the algorithm utilized to solve the configurations, methods, equations used and GUI features implementation are all described in this study. The case study considered for a four-bar mechanism indicates a strong agreement between the results obtained from the proposed kinematics-based simulator and ANSYS software. These results demonstrate the simulator's effectiveness in providing low-cost and user-friendly simulation results for various generic mechanisms involving multiple interconnected loops. [ABSTRACT FROM AUTHOR]

In this paper, the first‐order fractional step finite element method to solve the 2D/3D unstationary incompressible thermomicropolar fluid equations (ITME) is proposed. At each time step, the projection strategy about the linear velocity is adopted to get the linear velocity and pressure values in the first two sub‐steps, and then the angular velocity and temperature values are solved in the last two sub‐steps. Based on the proposed method, the variational problem is decomposed into four linear subproblems. By using the energy analysis technique, the unconditional stability and error estimates about the first‐order semi‐discrete method are derived, and the unconditional stability about the first‐order fully discrete method is analyzed. Finally, some numerical experiments are carried out to show the feasibility and effectiveness of the method. [ABSTRACT FROM AUTHOR]

To ensure the safety and energy efficiency of autonomous sampling operations for a deep-sea landing vehicle (DSLV), the Safety Energy-Dynamic Window Approach (SE-DWA) algorithm was proposed. The safety assessment sub-function formed from the warning obstacle zone and safety factor addresses the safety issue arising from the excessive range measurement error of forward-looking sonar. The trajectory comparison evaluation sub-function with the effect of reducing energy consumption achieves a reduction in path length by causing the predicted trajectory to deviate from the historical trajectory when encountering "U"-shaped obstacles. The pseudo-power evaluation sub-function with further energy consumption reduction ensures optimal linear and angular velocities by minimizing variables when encountering unknown obstacles. The simulation results demonstrate that compared with the Minimum Energy Consumption-DWA algorithm, the SE-DWA algorithm improves the minimum distance to an actual obstacle zone by 68% while reducing energy consumption by 11%. Both the SE-DWA algorithm and the Maximum Safety-DWA (MS-DWA) algorithm ensure operational safety with minimal distance to the actual obstacle zone, yet the SE-DWA algorithm achieves a 24% decrease in energy consumption. In conclusion, the path planned by the SE-DWA algorithm ensures not only safety but also energy consumption reduction during autonomous sampling operations by a DSLV in the deep sea. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm for the kinematics and statics analysis of a Gough–Stewart platform. Through defining the velocity screw, the relative angular and linear velocities of a single rigid body can be expressed as a single vector. The velocity screw equations of various mechanisms are deduced in detail, the forward and inverse kinematics of a parallel mechanism can be solved through the velocity screw equation. Similarly, the definition of the force screw allows all constraint forces and torques of a single rigid body to be expressed using a single vector, and the static screw equation can be used to solve the forward and inverse statics of a parallel mechanism in one coordinate system. The advantage of this approach is that kinematics and statics modeling are unified in screw coordinates because the kinematic parameters in screw form can be directly employed in statics modeling. The results of the kinematics and statics analysis of the Gough-Stewart platform validate this method. This algorithm is easy to compute and program with high efficiency, and it can also be applied to any other spatial, complex multi-rigid-body systems. [ABSTRACT FROM AUTHOR]

A ball rolled over a shallow step will experience an increase in velocity along the direction perpendicular to the step. We work with shallow step heights relative to the radius of the ball so that the motion of the ball is easy to observe at all times, and so that the ball does not bounce when it encounters the lower platform. At the instant the ball contacts the lower platform, it has an I x i -direction linear velocity of I v i SB e sb cos I i and a I z i -direction angular velocity of I i = - I v i SB e sb / I R i . [Extracted from the article]

In this paper, an intelligent nonholonomic wheeled mobile robot (WMR) for real-time trajectory tracking and dynamic obstacle avoidance is developed. The tracking controller of the WMR is designed based on the Takagi–Sugeno (T–S) fuzzy model. A handheld device adopted as the tracking object of the WMR is developed to measure the distance between the WMR and tracking object. The linear and angular velocities of the tracking object are incorporated into the dynamic model of the WMR; subsequently, the state equation of the attitude error of the WMR can be obtained. For obstacle avoidance, the deep image algorithm is utilized to estimate the distance between the WMR and obstacle. Next, the fixed-point tracking algorithm is used for object avoidance in indoor and outdoor environments. The simulation results reveal that the attitude error between the WMR and tracking object for dynamic tracking can converge to zero after a few seconds. Experimental results are provided to demonstrate the effectiveness and feasibility of the designed WMR and handheld device. [ABSTRACT FROM AUTHOR]

There is a great demand for vision-based robotics solutions that can operate using Global Positioning Systems (GPS), but are also robust against GPS signal loss and gyroscope failure. This paper investigates the estimation and tracking control in application to a Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV) in six degrees of freedom (6 DoF). A full state observer for the estimation of VTOL-UAV motion parameters (attitude, angular velocity, position, and linear velocity) is proposed on the Lie Group of S E 2 (3) × R 3 = S O (3) × R 9 with almost globally exponentially stable closed-loop error signals. Thereafter, a full state observer-based controller for the VTOL-UAV motion parameters is proposed on the Lie Group with a guaranteed almost global exponential stability. The proposed approach produces good results without the need for angular and linear velocity measurements (without a gyroscope and GPS signals) utilising only a set of known landmarks obtained by a vision-aided unit (monocular or stereo camera). The equivalent quaternion representation on S 3 × R 9 is provided in the Appendix. The observer-based controller is presented in a continuous form while its discrete version is tested using a VTOL-UAV simulation that incorporates large initial error and uncertain measurements. The proposed observer is additionally tested experimentally on a real-world UAV flight dataset. [ABSTRACT FROM AUTHOR]

Transient flows of micropolar fluids through circular domains are investigated. The flow domain has two annular regions. The outer region is clean, while the inner region contains a porous medium. The analytical solutions in closed forms for the linear and angular velocities in both regions are determined using the Laplace transform and finite Hankel integral transform under the assumptions of the continuity of the velocities, stresses, and couple stresses on the interface. The obtained solutions are new in the literature and can generate solutions for some particular cases of filtration processes involving polymeric fluids with additives or other fluids that show similarities to micropolar fluids. Effects of various parameters on the fluid motion have been investigated by numerical simulations and graphical illustrations. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose laws of trephine operation based on a robot-assisted cutting cornea in order to obtain better microsurgical effects for keratoplasty. Using a trephine robot integrated with a microforce sensor and a handheld trephine manipulator, robotic and manual experiments were performed, with porcine corneas as the test subjects. The effect of trephine operational parameters on the results reflected by the biomechanical response is discussed, and the parameters include linear velocity, rotating angle, and angular velocity. Using probability density functions, the distributions of the manual operational parameters show some randomness, and there is a large fluctuation in the trephine force during the experiments. The biomechanical response shows regular trends in the robotic experiments even under different parameters, and compared to manual trephination, the robot may perform the operation of trephine cornea cutting more stably. Under different operational parameters, the cutting force shows different trends, and the optimal initial parameters that result in better trephine effects can be obtained based on the trends. Based on this derived law, the operational parameters can be set in robotic trephination, and surgeons can also be specially trained to achieve a better microsurgical result. [ABSTRACT FROM AUTHOR]

Recently, navigation in an unknown environment without hitting obstacles was considered a big challenge faced by researchers. The difficulty in finding a good mathematical model for the different systems is deciding to use artificial intelligent controllers to control the mobile robot movement. In this paper, designing two multi-layer-perceptron neural networks (MLP-NN) was done to control the movement of mobile robots in an unknown environment. The first MLP-NN is to control the linear velocity on the x-axis and angular velocity of the robot's movement while the other MLP-NN is designed to avoid the static and dynamic obstacles faced by the robot while navigating in an unknown environment. The results show each controller's advantages in performing navigation tasks and avoiding obstacles in different environments. [ABSTRACT FROM AUTHOR]

This study discusses the problem of reducing the influence of external destabilizing factors on microelectromechanical angular velocity transducers. It reveals that for measurements of small angular velocities of the order of a few to tens of microradians per second, micro optoelectromechanical transducers that contain optical readout units are preferable to use. The effect of linear acceleration on the characteristics of a frame micro optoelectromechanical angular velocity transducer with two optical readout channels is analyzed. We consider two methods of angular velocity measurement error compensation when the frame micro optoelectromechanical transducer is under the influence of linear acceleration. The two compensation methods implement amplification factor control and force feedback, respectively. The readout unit, based on the optical tunnel effect and used for precision measurement of the amplitude of oscillations of the sensing element, is experimentally investigated; a function of converting the amplitude of oscillations of the sensing element into voltage is obtained. The possibility of forming transducer output signals, which are proportional to angular velocity and linear acceleration, is presented. The dependences of changes in the amplification factor on the zero off set voltage, proportional to the acting linear acceleration, are presented for different ranges of angular velocities. A system, consisting of a low-pass filter (LPF), a proportionalintegral regulator, and an additional pair of comb-type electrostatic actuators, is proposed for compensating the force effect of a destabilizing linear acceleration. Additional actuators are arranged perpendicular to the actuators that excite the primary oscillations. The measurement error of angular velocity when using the two methods of compensation, respectively, has been estimated. The proposed technical solutions enable to increase the accuracy of angular velocity measurements by micro optoelectromechanical transducers used in navigation and orientation systems of unmanned aircrafts of various types. [ABSTRACT FROM AUTHOR]

The bouncing process of an irregular object falling on the ground contains many interesting mechanical problems. The article investigated the bounce height of a capsule-shaped object when it falls on the ground. The variation of three physical quantities, namely the angle of the object, the linear velocity of the center of mass and the angular velocity relative to the center of mass when it fell on the ground are studied. According to the limit condition of friction, the three-dimensional phase diagram of the above three physical quantities was drawn when the fall height of the capsule-shaped object and the bounce height was equal. The movement of the capsule-shaped object is captured by using two cameras positioned perpendicular to each other. The trajectory was tracked by TRACKER software to obtain the fall height and bounce height of the capsule. When the bounce height was higher than the fall height, it was marked with a red dot. If both heights were equal, it was marked with a black dot. Otherwise, it was marked with a blue dot. Different types of experimental data points are plotted in the phase diagram. A large amount of random experimental data verifies the correctness of the theory. [ABSTRACT FROM AUTHOR]

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Object servoing is becoming more and more important for service robots. Because of the nonholonomic constraints of a differential-drive service robot and the possibly changed pose of a movable object, it is challenging to design an object servoing scheme for the differential-drive service robot such that it can asymptotically park at a predefined relative pose to that of the movable object. In this paper, a novel object servoing scheme is proposed for the differential-drive service robots using switched control. Each relative online pose is first estimated by using features of the movable object, the estimated pose is an input of an object servoing friendly parking controller. The linear velocity and angular speed are then determined by the proposed controller. Simulation results validate the performance of the proposed object servoing scheme. Due to its low online computational cost, the proposed scheme can be applied for the real-time tasks of differential-drive service robots to movable objects. [ABSTRACT FROM AUTHOR]

In complex orchard environments, orchard mowing robots are prone to longitudinal slippage because of the characteristics of tires and the adhesion conditions of the road surface, which makes it difficult for the robots to maintain high-precision path tracking and autonomous navigation positioning. This not only affects the accuracy of path tracking but also leads to unstable motion for the mowing robots. To solve the above problems, we take an orchard mowing robot as the control object and establish a cascaded path-tracking controller and an adaptive time domain model based on a kinematics model. By designing a linear error model, an objective function, and constraint conditions for the mowing robot, the optimal linear velocity and angular velocity of the mower are obtained and converted into the speed of the driving wheel. Then, an anti-slip driving controller is designed based on fuzzy control of the slip rate. The slip-rate-based fuzzy controller is constructed according to the real-time speed of the mower and the reference speed of the driving wheel solved by the model predictive controller, and anti-slip driving control is implemented through a combination of a PID controller and a tire dynamics model. To verify the effectiveness of the proposed method, simulation and field experiments are conducted. The experimental results show that the slip rate of the driving wheel of the mower remains within the target slip rate range in the orchard working environment, avoiding excessive driving wheel sliding. Furthermore, the average lateral error of the path-tracking controller is controlled within 0.05 m, and the average value of the longitudinal error is kept within 0.04 m, which satisfies the control accuracy requirements of lawn mower operations. The proposed method provides a reference optimization scheme for improving the path-tracking and motion stability of a mowing robot. [ABSTRACT FROM AUTHOR]

This study studies a critical issue that linear velocity and steering angular velocity of the wheels of omni-directional mobile robot are easily affected by the unknown external disturbances such as wind direction and road flatness during the visual servoing stabilization task. To overcome such challenging problems, this study proposes a disturbance observer based visual servoing control strategy. In configuration, the controller is divided into two parts: the quasi-min-max model predictive controller is designed to accommodate the state constraint and input constraint of the system, and complete the visual stabilization task without disturbance. A nonlinear disturbance observer is designed to estimate the external disturbance and feedback compensate the effect of the actual disturbance on the wheel speed. The simulation results and real experiments show that the proposed control strategy can stably accomplish the visual servoing stabilization task even with a large external disturbance. [ABSTRACT FROM AUTHOR]

Nanofluid comprises nanoparticles that have varied applications in several industries as well as science and engineering due to their heavier thermal conductivity in comparison to conventional fluids. In such applications the role of transportation is vital. However, biomedical applications such as the flow of blood in the human body, peristaltic pumping, processes, etc. the use of nanofluid are important. Therefore, the present investigation aims at the enhancement of thermophysical properties on the radiative micropolar nanofluid flow past a permeable moving surface. These physical properties are studied incorporating the concept of Koo–Kleinsteuer–Li (KKL) model. The crux of the study is the approximate analytical technique, that is, the Homotopy Perturbation Method (HPM). The illustration of the contributing parameters on the flow phenomena is obtained via graphical as well as tabular form. A comparative study is carried out for the good agreement of the present result with an earlier established result in a particular case. Some important findings of this work are a retardation in the linear velocity profile is observed due to increase in the volume fraction of the particle. Suction slows down the linear velocity profile whereas the impact is counter productive in case of injection. A hike in the angular velocity profile is seen in case of greater suction whereas the opposite effect is observed for injection. An increase in the thermal radiation boosts up the fluid temperature and as a result of this an increase in thermal layer thickness is observed. [ABSTRACT FROM AUTHOR]

This paper investigates the prescribed-time control problem for a class of wheeled mobile robot (WMR) subject to nonparametric skidding, slipping and input disturbance in an inner-outer loop framework. First, by backstepping approach, the virtual linear and angular velocities are acquired to follow the reference path to one special point. Then, different from the conventional ones for canonical integral cascade model, a novel prescribed-time extended state observer (PTESO) is designed for WMR such that the unknown skidding and slipping can be observed and compensated. By developing the active disturbance rejection control technique, the zero-error control is achieved for WMR in prescribed time instead of ultimately uniform boundedness. Moreover, the influence of the uncertainty is attenuated by the compensation scheme based on the PTESO estimation. Finally, some simulation results are presented to demonstrate the superiority and effectiveness of the developed method. [ABSTRACT FROM AUTHOR]

Maintaining a specific geometric formation during the movement is crucial for multiagent systems of mobile robots in various applications. Proper coordination can lead to reduced system costs, increased reliability and efficiency, and system adaptability and flexibility. This research proposes a novel movement coordination method for self-governing multiagent systems of intelligent mobile robots. The proposed method uses a leader-follower technique with a virtual leader to maintain a specific geometric structure. Additionally, the epsilon greedy algorithm is utilized to avoid loops. To reduce power consumption, it is proposed to turn on only a few robots' lidars at a time. They could drive all the robots in the group, allowing them to reach the goal without colliding with obstacles. Experiments on a complex map with nine robots were conducted to test the method's effectiveness. The success rate of the swarm reaching the target position and the number of steps needed were evaluated. Testing varied angular velocities of 1 to 20 degrees and linear velocities of 0.1 to 5.5 m/s. Results show the method effectively guides the robots without collisions. This method enables a group of self-governing multiagent systems of intelligent mobile robots to maintain a desired formation while avoiding obstacles and reducing power consumption. The results of the experimental study demonstrate the method's potential to be implemented in real-world missions and traffic management systems to increase efficiency and reduce costs. The proposed method can be utilized in military missions and traffic management systems, where maintaining a specific geometric formation is crucial. The method's ability to avoid obstacles and reduce power consumption can also lead to reduced costs and increased efficiency. [ABSTRACT FROM AUTHOR]

In order to improve the accuracy of robot terminal pose tracking and the anti-interference performance of robot nonlinear motion path control, a nonlinear output feedback control method based on neural network is proposed. Construct the coordinate transformation matrix of the connecting rod, calculate the linear and angular velocity of the nonlinear motion of the robot, then calculate the sum of the kinetic energy of each connecting rod of the robot, and establish the motion equation of the robot. The structure of BP neural network is analyzed, and the motion equation is solved by BP neural network. Finally, a Fractional Order PID controller is designed and BP neural network is constructed to control the nonlinear motion equation of the robot to complete the output feedback control of the robot. The experimental results show that the end attitude tracking error of this method is the smallest, and it best fits the actual nonlinear trajectory of the robot. It shows that this method can accurately track the end posture of the robot, and can still effectively control the trajectory of the robot in the interference environment. [ABSTRACT FROM AUTHOR]

This article proposes a decentralized controller for differential mobile robots, providing autonomous navigation and obstacle avoidance by enforcing a formation toward trajectory tracking. The control system relies on dynamic modeling, which integrates evasion forces from obstacles, formation forces, and path-following forces. The resulting control loop can be seen as a dynamic extension of the kinematic model for the differential mobile robot, producing linear and angular velocities fed to the mobile robot's kinematic model and thus passed to the low-level wheel controller. Using the Lyapunov method, the closed-loop stability is proven for the non-collision case. Experimental and simulated results that support the stability analysis and the performance of the proposed controller are shown. [ABSTRACT FROM AUTHOR]