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This paper aims to propose a novel method to identify the parameters of robotic manipulators using the torque exerted by the robot joint motors (measured by current sensors).

Previous studies used additional sensors like force sensor and inertia measurement unit, or additional payload mounted on the end-effector to perform parameter identification. The settings of these previous works were complicated. They could only identify part of the parameters. This paper uses the torque exerted by each joint while performing Fourier periodic excited trajectories. It divides the parameters into a linear part and a non-linear part, and uses linear least square (LLS) parameter estimation and dual-swarm-based particle swarm optimization (DPso) to compute the linear and non-linear parts, respectively.

The settings are simpler and can identify the dynamic parameters, the viscous friction coefficients and the Coulomb friction coefficients of two joints at the same time. A SIASUN 7-Axis Flexible Robot is used to experimentally validate the proposal. Comparison between the predicted torque values and ground-truth values of the joints confirms the effectiveness of the method.

The proposed method identifies two joints at the same time with satisfying precision and high efficiency. The identification errors of joints do not accumulate.

The purpose of this study is to analyze the nonlinear effects of corporate philanthropy on the responses of both internal and external stakeholders as well as its impact on corporate financial performance.

Based on the stakeholder theory, the authors developed a conceptual model to examine the nonlinear effects of corporate philanthropy on company performance. For the empirical analysis, data from 397 company-years was analyzed using a using a Heckman two-stage model. The robustness of the findings was also confirmed through panel regression analysis.

The study revealed a linear relationship between corporate reputation and corporate philanthropy, whereas job satisfaction exhibited a nonlinear relationship with corporate philanthropy.

This research bridges the gap in extant literature by scrutinizing the nonlinear associations between corporate philanthropy and financial performance. Additionally, it addresses an emerging scholarly demand to uncover the “dark side” of corporate philanthropy through an investigation into its adverse impacts on employee satisfaction. Moreover, the study augments existing understandings of stakeholder theory and corporate philanthropy, positing that the influence of corporate philanthropy, as conceptualized through stakeholder theory, hinges on perceived fairness in multilateral relationships.

This paper aims to improve the accuracy of robot payload identification and decrease the complexity in its industrial application by developing a new method based on the actuator current.

Instead of previous general robot dynamic modeling of the actuators, links, together with payload inertial parameters, the paper discovers that the difference of the actuator torque between the robot moving along the same trajectory with and without carrying payload can be described as a function of the payload inertial parameters directly. Then a direct dynamic identification model of payload is built, a set of specialized novel exciting trajectories are designed for accurate identification and the least square method is applied for the estimation of the load parameters.

The experiments confirm the effectiveness of the proposed method in robot payload identification. The identification accuracy is greatly improved compared with that of existing methods based on the actuator current and is close to the accuracy of the methods that direct use the wrist-mounted force-torque sensor.

As the provided experiments indicate, the proposed method expands the application range and greatly improves the accuracy, hence making payload identification fully operational in the industrial application.

The novelty of such an identification method is that it does not require the rotor inertias and inertial parameters of links as a prior knowledge, and the specially designed trajectories provide completed decoupling of the load parameters.

A minimum‐time path‐following algorithm for industrial robots is presented in this paper.

The algorithm generates off‐line a trajectory that, by exploiting knowledge of the dynamic model, takes into account the actuators' torque limits while preserving the geometric path.

The algorithm has been designed, implemented and extensively tested on a Comau SMART H4 robot, a closed‐chain six‐degree‐of‐freedom industrial manipulator.

The algorithm is currently part of the new generation of industrial controllers of the Comau robots, the C4G controller. It is a feature added as with the name SmartMove4.

The paper presents a new minimum‐time path‐following algorithm for industrial robots that, by exploiting knowledge of the dynamic model, takes into account the actuators' torque limits while preserving the geometric path.