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A 3-degrees-of-freedom cable-driven hybrid 3D-printing mechanism is developed to overcome the high inertia of rigid printing mechanisms and the difficulties of mechanism analysis, a vector analysis method is proposed, and a prescribed-performance controller is designed to improve the stability and motion accuracy of the end-effector. A physical simulation environment and a prototype of the mechanisms are developed. Finally, the clay-printing experiment results show the mechanism to be feasible.

The main contribution of this work is to propose a multi-objective optimization design method in terms of factor analysis, a back-propagation (BP) neural network, principal component analysis (PCA), and a particle swarm optimization (PSO) algorithm to achieve optimal comprehensive performance of a mechanism. The computational cost of the proposed approach was reduced by 96.95 % compared with the PSO algorithm, and the comprehensive performance increased by 118.92 %.

This paper proposes a robot following method to follow the sewing action of human upper limbs. The purpose of this paper is to demonstrate that robots can assist workers in the future. Compared with the visual servo method, the accuracy is much improved.

Aiming to address the noise reduction problem of two-speed automatic transmission of a pure electric vehicle, in the study, through the vehicle noise test, the noise source and noise cause were analyzed and the gear modification optimization method and the gear modification effect were explored.

In this paper, a gait analysis algorithm for a lower limb rehabilitation robot is proposed. The algorithm realizes the division of gait temporal information and the design of a gait spatiotemporal parameter algorithm based on lidar. A spatial parameter-splicing algorithm based on a time series is proposed, which effectively reduces the influence of errors on gait parameters. Based on the gait algorithm, aiming at real-time algorithm performance, a dynamic window method is proposed.

In the design and processing of face gears, it is not necessary to accurately express the tooth surface with an equation, since it will be difficult to analyze some of the most important and practical features, such as the induced curvature relationship. In this regard, this paper uses the discrete curvature relationship of a spatial gradient curvature ellipsoid to describe the space meshing surface, and it establishes a set of discrete digital conjugate surface meshing principles.

Considering its practical engineering applications, a proportional-derivative-based robust controller is designed and applied to a nonlinear robotic system with uncertainty. With error- and model-based features, accurate position tracking can be achieved. The control feedback gain is automatically and iteratively adjusted by learning so that the desired performance of the system is optimized.

A high-speed wheeled amphibious vehicle was designed and researched based on computational fluid dynamic (CFD) technology. The results were compared with the corresponding test results for verification. CFD is applied to analyze the influence of the wheel flip angle on the resistance performance, and resistance reduction is explained by the change in wake flow-field of the amphibious vehicle. The wheel well was optimized based on our requirement for the vehicle performance on land and water.

In order to reduce the energy loss and improve the wear resistance of a piston–cylinder pair in an axial piston motor，an optimized tapered piston bore is designed and applied. A fluid–structure interaction numerical model and a new test rig of the friction force of the piston–cylinder pair are developed. Numerical analysis and experimental results show that the optimized tapered-shape piston bore in an axial piston motor can achieve a significant reduction in leakage flow and friction force.

Obstacle avoidance and path-tracking control of intelligent vehicles have always been the key issues of intelligent vehicles. This paper improves the traditional model predictive control algorithm. According to the simulation results, compared with the traditional model predictive control, the proposed adaptive model predictive control algorithm can not only avoid obstacles, but also improve the vehicle path-tracking accuracy and driving stability.