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The purpose of this paper is to enable autonomous door-opening with unknown geometrical constraints. Door-opening is a common action needed for mobile manipulators to perform rescue operation. However, it remains difficult for them to handle it in real rescue environments. The major difficulties of rescue manipulation involve contradiction between unknown geometrical constraints and limited sensors because of extreme physical constraints.

A method for estimating the unknown door geometrical parameters using coordinate transformation of the end-effector with visual teleoperation assists is proposed. A trajectory planning algorithm is developed using geometrical parameters from the proposed method.

The relevant experiments are also conducted using a manipulator suited to extreme physical constraints to open a real door with a locked latch and unknown geometrical parameters, which demonstrates the validity and efficiency of the proposed approach.

This is a novel method for estimating the unknown door geometrical parameters with coordinate transformation of the end-effector through visual teleoperation assists.

Calibrating kinematic parameters is one of the efficient ways to improve the robot's positioning accuracy. A method based on the product-of-exponential (POE) formula to calibrate the kinematic parameters of serial industrial robots is proposed. The paper aims to discuss these issues.

The forward kinematics is established, and the general positioning error model is deduced in an explicit expression. A simplified model of robot's positioning error is established as both the error of reference configuration and the error of rigid displacement of the base coordinating system with respect to the measuring coordinating system are equivalently transferred to the zero position errors of the robot's joints. A practical calibration model is forwarded only requiring 3D measuring based on least-squares algorithm. The calibration system and strategy for calibrating kinematic parameters are designed.

By the two geometrical constrains between the twist coordinates, each joint twist only has four independent coordinates. Due to the equivalent error model, the zero position error of each joint can cover the error of reference configuration and rigid displacement of the robot base coordinating system with respect to the measuring coordinating system. The appropriate number of independent kinematic parameters of each joint to be calibrated is five.

It is proved by a group of calibration experiments that the calibration method is well conditioned and can be used to promote the level of absolute error of end effector of industrial robot to 2.2 mm.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

In this paper, the authors design accelerated life test and provide its application in the field of accelerated life test. The authors use maximum likelihood estimation method as a parameter estimation method.

In this paper we design accelerated life test and provide its application in the field of accelerated life test. The authors use maximum likelihood estimation method as a parameter estimation method.

In this study, the authors design accelerated life test under Type-I censoring when the lifetime of test items follows PID and also provides its application in the field of warranty policy. The following conclusion is made on the basis of this study. (1) An inverse relationship is shown between the shape parameter with the expected total cost and expected cycle time, while the shape parameter directly relates to the expected cost rate (see Table 5). (2) A direct relationship is shown between the scale parameter with the expected total cost and expected time cycle, while the inverse relationship is shown with the expected cost rate (see Table 5). (3) An inverse relationship is shown between the replacement age and the expected cost rate, while there are direct relationships between expected total cost and expected time cycle (see Table 5).

This paper is neither published or neither accepted anywhere.

This paper aims to propose a novel robot kinematic calibration method based on the common perpendicular line (CPL) model to improve the absolute accuracy of industrial robots.

The deviation between the nominal and actual twists is considered the CPL transformation, which includes the rotation about the CPL and the translation along the CPL. By using the invariance of the reciprocal product of the two spatial lines, the previous deviation was analyzed in the neighbor space of the base frame origin. In this space, the line vector of the CPL contained only four independent parameters: two orientation elements and two moment elements. Thus, the CPL model has four independent parameters for the revolute joint and two parameters for the prismatic joint.

By simulations and experiment conducted on a SCARA robot and a 6-DOF PUMA robot, the effectiveness of the novel method for calibration of industrial robot is validated.

The CPL model avoided the normalization and orthogonalization in the iterative identification procedure. Therefore, identifying the CPL model was not only simpler but also more accurate than that of the traditional model. In addition, the results of the CPL transformation strictly conformed to the constraints of the twist.

Describes an innovative error compensation method to improve the static positioning accuracy of industrial robots or other servo‐driven manipulation devices. As well as the theoretical formulation, shows experimental results for quantitative estimation and verification of the method. Outlines integration concepts for this error compensation technique within commercial robot controllers.

Some of the fundamental problems associated with the aerodynamic configuration of a single‐rotor remotely piloted helicopter are discussed in this paper. A method for selecting the aerodynamic shape of a fuselage and determining the locations and parameters of a horizontal stabilizer and a tail rotor in the preliminary design analysis is given. The application of this method to a remotely piloted single main rotor and tail rotor helicopter developed at the Nanjing University of Aeronautics and Astronautics is described. A raindrop shaped fuselage is chosen for the remotely piloted helicopter and the low drag characteristics of the fuselage are demonstrated from the wind‐tunnel experimental data. The experimental results on the pitching moment characteristics of the horizontal stabilizer are also presented and analyzed. The design considerations of the horizontal stabilizer and tail rotor of the helicopter are discussed in detail.

The purpose of this study is to present a new and relatively inexpensive method for posture evaluation of the positioning of the wing-body assembly. Positioning is an essential process to guarantee alignment accuracy in an assembly line.

The studied method includes a structural set-up and a software algorithm used to process a set of experimental input data to compute the actual position of the wing with respect to the ideal position, which is proposed considering measurement uncertainty, the deviation caused by large errors in measurement points and the different tolerance requirements.

The studied method has been found to be simple and effective in addition to being highly accurate. Compared with most of the current methods that have been developed with optical equipment, it is more cost- and space-efficient. The automation process determines how much operation time will be saved.

The studied method has been applied in an actual assembly line, and the economic and time savings illustrate its benefits.

This method provides an attractive wing-body assembly solution for those enterprises that want to find a low-cost option or have limited measuring space for optical equipment. It can also be the basis for the accurate assembly of other large parts for aircraft and other vessels.

Discusses robot accuracy and repeatability and the mechanical and control aspects of robots that lead to errors occuring in static positioning and dynamic path following. Outlines the steps that should be taken to minimise errors and concludes that robot users should encourage manufacturers to utilize the ISO and ANSI standards when measuring and presenting robot capabilities. This will not only give users the ability to objectively compare systems, but also push robot manufacturers to develop a better understanding of the products they are selling.

This paper aims to present a complete relative pose error model for robot calibration, considering both the relative distance error and the relative rotation error of the robot end-effector, which can improve calibration accuracy.

In this paper, the relative distance error model and the relative rotation error model of robot calibration are derived by ignoring high-order nonlinear errors, and the two models form into a complete relative pose error model. Besides, mathematical expectation of the nonlinear errors is calculated, indicating that they have little influence on calibration accuracy.

Comparative experiments have indicated that the proposed complete relative pose error model does better in robot calibration than only the distance error model.

The main contribution of this paper lies in the derivation of the relative rotation error model, which helps to form a complete relative pose error model for calibration. The proposed method improves calibration accuracy, with avoiding identifying the transformation matrix between the measurement system frame and the robot base frame.