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In order to explore the complex thermal characteristics of five-axis NC (numerical control) machine tools, a method for thermal error modeling of cradle five-axis NC machine tools was proposed. The principle of shark smell optimization (SSO) algorithm and neural network composite modeling was adopted, which effectively improved the accuracy and modeling efficiency of the machine tool thermal error prediction model. Firstly, the temperature sensitive point was screened by using the thermal imager, and then the temperature sensor was placed at the position of the heat sensitive point of the machine tool. The collected thermal characteristic data were modeled by the above method. The results showed that the method is better than ABC neural network and PSO neural network in terms of modeling speed and accuracy. Finally, the model was applied to the thermal error compensation experiment of the five-axis machine tool, which improves its accuracy by 32%. [ABSTRACT FROM AUTHOR] more...

In order to meet the requirements of quadruped robots' leg structure with high cushion performance in running movements， a leg structure of running quadruped robots was designed， which was based on the bone-muscle biomechanical properties of dog forelegs. The leg structure has three joints and three DOFs. The hip joint and knee joint have active pitching-DOF， and the ankle joint has passive pitching-DOF. The dynamics and stiffness characteristics of the leg structure were analyzed， and the simulation of bound gait was done. The simulation results showed that a quadruped robot with this leg structure can run rapidly and stably while the joint drive torque is low. It was proven that this leg structure has the feasibility and rationality of making quadruped robots run in bound gait. [ABSTRACT FROM AUTHOR] more...

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