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The purpose of this paper is to analyze the sensitivity of the motion error parameters in microassembly process, thereby improving the assembly accuracy. The motion errors of the precision motion stages directly affect the final assembly quality after the machine visual alignment.

This paper presents the error parameters of the in-house microassembly system with coaxial alignment function, builds the error transfer model by the multi-body system theory, analyzes the error sensitivity on the sensitive direction using the Sobol method, which was based on variance, and then gets the ones which made a great degree of influence. Before the sensitivity analyzing, parts of the error sources have been measured to obtain their distribution ranges.

The results of the sensitivity analysis by the Sobol method, which was based on variance, are coincident with the theoretical analysis. Besides, the results provide a reference for the error compensation in control process, for the selection of the precision motion stages and for the installation index of the motion stages of the assembly system with coaxial alignment.

This kind of error sensitivity analysis method is of great significance for improving the assembly accuracy after visual system positioning, and increasing efficiency from the initial motion stage selection to final error compensation for designers. It is suitable for general precision motion systems be of multi-degree of freedom, for the method of modeling, measuring and analyzing used in this paper are all universal and applicative.

This study aims to explore the impact of multisource deformation errors on the oil film contact surface, which arise from manufacturing, assembly, oil pressure and thermal influences, on the motion accuracy of hydrostatic guideway.

Using thermal-structural coupling simulations, this research investigates the effects of assembly, oil pressure and thermal factors on deformation errors of the oil film contact surface. By integrating these with manufacturing errors, a profile error model for the oil film contact surface is developed, characterizing the cumulative effect of these errors. Using kinematic theory and progressive Mengen flow controller characteristics, the motion error at any position of the hydrostatic guideway is quantified, examining how surface error traits impact motion accuracy.

The error averaging effect is affected by the profile error of oil film contact surface. Meanwhile, the motion accuracy of hydrostatic guideway is highly sensitive to the oil film contact surface error amplitude.

This approach allows for precise prediction and analysis of motion accuracy in hydrostatic guideways during the design and manufacturing stages. It also provides guidance for planning process tolerances.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0063/

The purpose of this paper is to search the optimal arrangement scheme of random motion accuracy of joints for optimal synthesis of pose repeatability which can make robot design more reasonable and reduce the development cost of robots.

In this paper, a mathematical model of pose repeatability, which includes positioning repeatability and orientation repeatability of robots, is established. According to the ISO 9283 standard, an optimal synthesis method of pose repeatability for collaborative robots is introduced, and three optimization objective functions are proposed. The optimization model is solved by using numerical analysis software, and the optimal arrangement scheme of random motion accuracy of joints is obtained which meets the requirements of pose repeatability of robot.

It is found that, in three optimization objective functions, the single-objective evaluation function of maximization of joint motion error is more suitable for optimal synthesis of pose repeatability. In practice, due to the safety factor, the test results of pose repeatability are better than the results of optimal synthesis of pose repeatability.

This method makes robot design more reasonable and reduces the development cost of robots.

This work is the first time to optimize the orientation repeatability of collaborative robots. Because the pose repeatability of most robots is tested by the ISO 9283 standard, so this method which is based on this standard is more suitable for the performance requirements of robot products.

Uncertainty can arise for a manipulator because its motion can deviate unpredictably from the assumed dynamical model and because sensors might provide information regarding the system state that is imperfect because of noise and imprecise measurement. This paper aims to propose a method to estimate the probable error ranges of the entire trajectory for a manipulator with motion and sensor uncertainties. The aims are to evaluate whether a manipulator can safely avoid all obstacles under uncertain conditions and to determine the probability that the end effector arrives at its goal area.

An effective, analytical method is presented to evaluate the trajectory error correctly, and a motion plan was executed using Gaussian models by considering sensor and motion uncertainties. The method used an integrated algorithm that combined a Gaussian error model with an extended Kalman filter and a linear–quadratic regulator. Iterative linearization of the nonlinear dynamics was used around every section of the trajectory to derive all of the prior probability distributions before execution.

Simulation and experimental results indicate that the proposed trajectory planning method based on the motion and sensor uncertainties is indeed highly convenient and efficient.

The proposed approach is applicable to manipulators with motion and sensor uncertainties. It helps determine the error distribution of the predefined trajectory. Based on the evaluation results, the most appropriate trajectory can be selected among many predefined trajectories according to the error ranges and the probability of arriving at the goal area. The method has been successfully applied to a manipulator operating on the Chinese Space Station.

THE accountant is the latest competitor for management power. The Institute of Cost & Works Accountants—the value of whose Associate qualification we acknowledge—has re‐cast its requirements for the grade of Fellowship. Cost Accountants' or for that matter many other kinds of accountant, are now invited to sit for the Fellowship examination, the syllabus for which has just been published. This comprises the now familiar: Management—Factory and Distribution, Statistical Method, Advanced Cost Accountancy, Company Law, Management Accountancy and the Economic Aspects of Industry and Commerce. (The Management Section includes Motion & Time Study). Assuming that they are successful in this and that they satisfy a Reviewing Board of the adequacy of their experience, they may then call themselves “Management Accountants”.

The purpose of this paper is to present work which is a part of the Comprehensive Automation for Specialty Crops project (CASC). Desired trajectory tracking objective has been previously performed by using a non‐model based approach in this project. Long distance autonomous drive has been achieved; however the results haven't met the expectations of the project requirements. In order to provide these requirements, this study is conducted. In this study, long distance autonomous trajectory tracking for an orchard vehicle is studied. Besides longitudinal motion, lateral motion of the vehicle is also considered. The longitudinal and lateral errors are objected to keep into a region of less than 10 cm.

Car‐like robot kinematic modeling approach is used to create desired trajectory. In order to control longitudinal velocity and steering angle of the vehicle, a controller methodology is proposed. Stability of the controller proposed is shown by using Lyapunov stability approach.

The proposed model is adapted into a four‐wheeled autonomous orchard vehicle and tested in an experimental orchard for long distance autonomous drives. More than 15 km autonomous drive is successfully achieved and the details are presented in this paper.

In this study, long distance autonomous trajectory tracking for an orchard vehicle is focused. A model based control strategy, including the information about longitudinal and lateral motion of the vehicle, is constructed. A new approach to create steering angles for turning operations of the orchard vehicle is introduced. It is objected that the longitudinal and lateral errors should be less than 10 cm during the trajectory tracking task.

The mechanical properties between wheel and ground will affect the motion performance of wheeled omnidirectional mobile robot (OMR). MY3 wheel is an omnidirectional wheel. This paper aims to analyze the contact mechanical characteristics between MY3 wheel and ground to improve the motion accuracy of an omnidirectional mobile platform with MY3 wheel (MY3-OMR).

This method takes MY3 wheel as the research objective. The normal and tangential contact mechanics model and rolling contact mechanics model of MY3 wheel are established by analyzing the structure of MY3 wheel, and thereby, the slip ratio of MY3 wheel in the process of motion is calculated. The kinematics model of MY3-OMR is optimized by taking the slip ratio as the optimization parameter that aims to improve motion accuracy of MY3-OMR.

The correctness of the mechanical analysis and the feasibility of the method are verified by the MY3-OMR prototype. Let MY3-OMR move along the set circular trajectory and square trajectory, and the error between the motion trajectory before and after optimization and the standard trajectory is obtained. It illustrates that the error in the square trajectory is reduced by 1.5%, and the circular trajectory error is reduced by 2%; therefore, the method is effective.

A method based on contact mechanics is proposed and verified. Through the establishment of wheel-ground contact mechanics model to optimize MY3-OMR kinematics model, and thereby, the motion accuracy of MY3-OMR is improved, which lays a foundation for MY3-OMR engineering application.

The purpose of this paper is to describe a novel application of the recently introduced concept from computer vision to self‐localization of a walking robot in unstructured environments. The technique described in this paper enables a walking robot with a monocular vision system (single camera) to obtain precise estimates of its pose with regard to the six degrees of freedom. This capability is essential in search and rescue missions in collapsed buildings, polluted industrial plants, etc.

The Parallel Tracking and Mapping (PTAM) algorithm and the Inertial Measurement Unit (IMU) are used to determine the 6‐d.o.f. pose of a walking robot. Bundle‐adjustment‐based tracking and structure reconstruction are applied to obtain precise camera poses from the monocular vision data. The inclination of the robot's platform is determined by using IMU. The self‐localization system is used together with the RRT‐based motion planner, which allows to walk autonomously on rough, previously unknown terrain. The presented system operates on‐line on the real hexapod robot. Efficiency and precision of the proposed solution are demonstrated by experimental data.

The PTAM‐based self‐localization system enables the robot to walk autonomously on rough terrain. The software operates on‐line and can be implemented on the robot's on‐board PC. Results of the experiments show that the position error is small enough to allow robust elevation mapping using the laser scanner. In spite of the unavoidable feet slippages, the walking robot which uses PTAM for self‐localization can precisely estimate its position and successfully recover from motion execution errors.

So far the presented self‐localization system was tested in limited‐scale indoor experiments. Experiments with more realistic outdoor scenarios are scheduled as further work.

Precise self‐localization may be one of the most important factors enabling the use of walking robots in practical USAR missions. The results of research on precise self‐localization in 6‐d.o.f. may be also useful for autonomous robots in other application areas: construction, agriculture, military.

The vision‐based self‐localization algorithm used in the presented research is not new, but the contribution lies in its implementation/integration on a walking robot, and experimental evaluation in the demanding problem of precise self‐localization in rough terrain.

A flight simulator must be designed to generate the correct acceleration cues, attitudes and vibrations to the flight compartment to provide an extra degree of realism for the pilots. Therefore, such a system, which has six degrees of freedom (dof), should enable to produce pitch, roll, yaw, heave, forward and lateral movement simultaneously. However, such a complex dynamic system can be modeled as a Stewart platform with pneumatic actuators, having six dof. During the simulations, on the position and orientation of moving platform, motion determination parameters and their absolute, relative errors and standard deviations are outlined. Simulation results, which are obtained, when closely examined reveal that the developed motion determination algorithm for the considered parallel dynamic mechanism is highly accurate. Additionally, a technique is introduced for the motion determination and its deviation from the given task.

This paper is motivated by the need for a generic approach to evaluate the volumetric accuracy of rapid prototyping (RP) machines. The approach presented in this paper is inspired in large part by the techniques developed over the years for the parametric evaluation of coordinate measuring machine (CMM) errors. In CMM metrology, the parametric error functions for the machine are determined by actual measurement of a master reference artifact with known characteristics. In our approach, the RP machine is used to produce a generic artifact, which is then measured by a master CMM, and measurement results are used to infer the RP machine's parametric error functions. The results presented demonstrate the feasibility of such an approach on a two‐dimensional model.