Perfect base makeup is the guarantee of exquisite makeup.However,the problem of base makeup darkening seriously affects the cosmetic effect,and also troubles many researchers and consumers.In this paper,a basic liquid...Perfect base makeup is the guarantee of exquisite makeup.However,the problem of base makeup darkening seriously affects the cosmetic effect,and also troubles many researchers and consumers.In this paper,a basic liquid foundation was chosen as model to explore the darkness reason from the aspects of foundation hue,volatility of emulsification system,and sebum secretion.DEcmc value determined by non-contact colorimeter was used to monitor the process of darkness.It’s widely accepted that foundation oxidation is key to darkness.We herein report a new insight into the essential reason of darkness due to the interaction between light and foundation.The red hue of the foundation darkened faster because the human eyes were more sensitive to the color difference of red.The volatility of foundation emulsion system and skin sebum secretion accelerated the foundation darkening process,which was caused by the change of foundation surface structure.Considering the above influencing factors,the formula was adjusted and an improved formula was proposed,which could significantly reduce the process of foundation darkening.展开更多
In order to help the operator perform the human-robot collaboration task and optimize the task performance,an adaptive control method based on optimal admittance parameters is proposed.The overall control structure wi...In order to help the operator perform the human-robot collaboration task and optimize the task performance,an adaptive control method based on optimal admittance parameters is proposed.The overall control structure with the inner loop and outer loop is first established.The tasks of the inner loop and outer loop are robot control and task optimization,respectively.An inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is then proposed,which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator.Subsequently,the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force.The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model.The model includes the unknown dynamics of the operator and the task performance details.To relax the requirement of the system model,the integral reinforcement learning is employed to solve the linear quadratic regulator problem.Besides,an auxiliary force is designed to help the operator complete the specific task better.Compared with the traditional control scheme,the security performance and interaction performance of the human-robot collaboration system are improved.The effectiveness of the proposed method is verified through two numerical simulations.In addition,a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.展开更多
文摘Perfect base makeup is the guarantee of exquisite makeup.However,the problem of base makeup darkening seriously affects the cosmetic effect,and also troubles many researchers and consumers.In this paper,a basic liquid foundation was chosen as model to explore the darkness reason from the aspects of foundation hue,volatility of emulsification system,and sebum secretion.DEcmc value determined by non-contact colorimeter was used to monitor the process of darkness.It’s widely accepted that foundation oxidation is key to darkness.We herein report a new insight into the essential reason of darkness due to the interaction between light and foundation.The red hue of the foundation darkened faster because the human eyes were more sensitive to the color difference of red.The volatility of foundation emulsion system and skin sebum secretion accelerated the foundation darkening process,which was caused by the change of foundation surface structure.Considering the above influencing factors,the formula was adjusted and an improved formula was proposed,which could significantly reduce the process of foundation darkening.
基金the National Key R&D Program of China(No.2018YFB1308400)the Natural Science Foundation of Zhejiang Province(No.LY21F030018)。
文摘In order to help the operator perform the human-robot collaboration task and optimize the task performance,an adaptive control method based on optimal admittance parameters is proposed.The overall control structure with the inner loop and outer loop is first established.The tasks of the inner loop and outer loop are robot control and task optimization,respectively.An inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is then proposed,which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator.Subsequently,the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force.The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model.The model includes the unknown dynamics of the operator and the task performance details.To relax the requirement of the system model,the integral reinforcement learning is employed to solve the linear quadratic regulator problem.Besides,an auxiliary force is designed to help the operator complete the specific task better.Compared with the traditional control scheme,the security performance and interaction performance of the human-robot collaboration system are improved.The effectiveness of the proposed method is verified through two numerical simulations.In addition,a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.
