Parallel manipulator systems as promising precision devices are used widely in current researches. A novel large workspace flexure parallel manipulator system utilizing wide-range flexure hinges as passive joints is p...Parallel manipulator systems as promising precision devices are used widely in current researches. A novel large workspace flexure parallel manipulator system utilizing wide-range flexure hinges as passive joints is proposed in this paper, which can attain sub-micron-seale precision over the cubic centimeter motion range. This paper introduces the mechanical system architecture based on the wide-range flexure hinges, analyzes the kinematics via stiffness matrices, presents the control system configuration and control strategy, and finally gives the system performance test results.展开更多
A density matrix is usually obtained by solving the Bloch equation, however only a few Hamiltonians＇ density matrices can be analytically derived. The density matrix for two interacting particles with kinetic couplin...A density matrix is usually obtained by solving the Bloch equation, however only a few Hamiltonians＇ density matrices can be analytically derived. The density matrix for two interacting particles with kinetic coupling is hard to derive by the usual method due to this coupling; this paper solves this problem by using the bipartite entangled state representation.展开更多
Multibody musculoskeletal modeling of human gait has been proved helpful in investigating the pathology of musculoskeletal disorders.However,conventional inverse dynamics methods rely on external force sensors and can...Multibody musculoskeletal modeling of human gait has been proved helpful in investigating the pathology of musculoskeletal disorders.However,conventional inverse dynamics methods rely on external force sensors and cannot capture the nonlinear muscle behaviors.Meanwhile,the forward dynamics approach is computationally demanding and only suited for relatively simple tasks.This study proposed an integrated simulation methodology to fulfill the requirements of estimating foot-ground reaction force,tendon elasticity,and muscle recruitment optimization.A hybrid motion capture system,which combines the marker-based infrared device and markerless tracking through deep convolutional neural networks,was developed to track lower limb movements.The foot-ground reaction forces were determined by a contact model for soft materials,and its parameters were estimated using a two-step optimization method.The muscle recruitment problem was first resolved via a static optimization algorithm,and the obtained muscle activations were used as initial values for further simulation.A torque tracking procedure was then performed by minimizing the errors of joint torques calculated by musculotendon equilibrium equations and inverse dynamics.The proposed approach was validated against the electromyography measurements of a healthy subject during gait.The simulation framework provides a robust way of predicting joint torques,musculotendon forces,and muscle activations,which can be beneficial for understanding the biomechanics of normal and pathological gait.展开更多
文摘Parallel manipulator systems as promising precision devices are used widely in current researches. A novel large workspace flexure parallel manipulator system utilizing wide-range flexure hinges as passive joints is proposed in this paper, which can attain sub-micron-seale precision over the cubic centimeter motion range. This paper introduces the mechanical system architecture based on the wide-range flexure hinges, analyzes the kinematics via stiffness matrices, presents the control system configuration and control strategy, and finally gives the system performance test results.
文摘A density matrix is usually obtained by solving the Bloch equation, however only a few Hamiltonians＇ density matrices can be analytically derived. The density matrix for two interacting particles with kinetic coupling is hard to derive by the usual method due to this coupling; this paper solves this problem by using the bipartite entangled state representation.
基金the National Natural Science Foundations of China(Grant Nos.12102035 and 12125201)the China Postdoctoral Science Foundation(Grant No.2020TQ0042)the Beijing Natural Science Foundation(Grant No.L212008).
文摘Multibody musculoskeletal modeling of human gait has been proved helpful in investigating the pathology of musculoskeletal disorders.However,conventional inverse dynamics methods rely on external force sensors and cannot capture the nonlinear muscle behaviors.Meanwhile,the forward dynamics approach is computationally demanding and only suited for relatively simple tasks.This study proposed an integrated simulation methodology to fulfill the requirements of estimating foot-ground reaction force,tendon elasticity,and muscle recruitment optimization.A hybrid motion capture system,which combines the marker-based infrared device and markerless tracking through deep convolutional neural networks,was developed to track lower limb movements.The foot-ground reaction forces were determined by a contact model for soft materials,and its parameters were estimated using a two-step optimization method.The muscle recruitment problem was first resolved via a static optimization algorithm,and the obtained muscle activations were used as initial values for further simulation.A torque tracking procedure was then performed by minimizing the errors of joint torques calculated by musculotendon equilibrium equations and inverse dynamics.The proposed approach was validated against the electromyography measurements of a healthy subject during gait.The simulation framework provides a robust way of predicting joint torques,musculotendon forces,and muscle activations,which can be beneficial for understanding the biomechanics of normal and pathological gait.
