The epicyclic gear train (EGT) is a gear transmission mechanism. When the number of designed structures is increasing and structures are becoming ever more complex, manual screening is very difficult. Therefore, scholars are committed to developing an algorithm that can distinguish repetitive structures. In this paper, we use a method to transform the structural information of EGT into a matrix and extract the hidden information in the matrix to judge whether there is a repeated structure.

Industrial robots are required to perform a given task repetitively with high tracking precision. Iterative learning control (ILC) calculates the tracking error of each iteration and corrects the output control signals in accordance with a predefined learning operator. This research considers the changes of the dynamics characteristics when the robot has different types of payload. It provides an approach for adaptation of the ILC to the specific payload to achieve faster convergence.

We present a novel exoskeleton based on deformable pneumatic actuators, known as McKibben muscles or artificial muscles. The aim of this system is to support a worker during overhead tasks, in which they need to lift the arms and hold that position for a long time. Simulations have been performed, starting from a mathematical model of the exoskeleton and of the artificial muscle. A first architecture of the complete device is also presented.

We introduce different test scenarios and set-ups for a force control assessment. The force control of Universal Robots (UR10e) and FerRobotics (ACF-K 109/04) are evaluated. A force/torque sensor, mounted below a work piece, measures the applied force by the UR or by the ACF. Results for both UR and ACF force control are presented for varying desired contact velocities and forces. These results show the advantage of the ACF-K 109/04 over the UR10e force control for highly dynamic scenarios.

Compared with the two traditional intelligent optimization algorithms, the results show that the particle swarm optimization configuration algorithm, based on an improved orthogonal experiment design, has a better optimization effect, and the results are improved to a certain extent. The evaluation indexes of a multi-objective optimization design are often contradictory. The designer needs to compromise and select an appropriate parameter design value.