In human-machine interaction,robotic hands are useful in many scenarios.To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction.Here,we ...In human-machine interaction,robotic hands are useful in many scenarios.To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction.Here,we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand.With a finger’s traction movement of flexion or extension,the sensor can induce positive/negative pulse signals.Through counting the pulses in unit time,the degree,speed,and direction of finger motion can be judged in realtime.The magnetic array plays an important role in generating the quantifiable pulses.The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway,respectively,thus improve the durability,low speed signal amplitude,and stability of the system.This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural,intuitive,and real-time human-robotic interaction.展开更多
Because of the special underwater environment, many sensors used well in robots working in space or on the land can not be used in the underwater. So an optical fiber type slide tactile sensor is designed by the inner...Because of the special underwater environment, many sensors used well in robots working in space or on the land can not be used in the underwater. So an optical fiber type slide tactile sensor is designed by the inner modulation mechanism of the intensity type optical fiber. The principle and structure of the sensor are introduced in detail. The static and dynamic characteristics are analyzed theoretically and experimentally. The dynamic characteristic model is built and the simulation is made by using genetic algorithm based on neural network. In order to use the sensor perfectly, the recognition model of the sensor is built on the basis of the principle of “inverse solution” using neural networks. The control precision and sensitivity of the manipulator are improved.展开更多
基金This work was supported by National Natural Science Foundation of China(51902035 and 52073037)Natural Science Foundation of Chongqing(cstc2020jcyj-msxmX0807)+1 种基金the Fundamental Research Funds for the Central Universities(2020CDJ-LHSS-001 and 2019CDXZWL001)Chongqing graduate tutor team construction project(ydstd1832).
文摘In human-machine interaction,robotic hands are useful in many scenarios.To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction.Here,we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand.With a finger’s traction movement of flexion or extension,the sensor can induce positive/negative pulse signals.Through counting the pulses in unit time,the degree,speed,and direction of finger motion can be judged in realtime.The magnetic array plays an important role in generating the quantifiable pulses.The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway,respectively,thus improve the durability,low speed signal amplitude,and stability of the system.This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural,intuitive,and real-time human-robotic interaction.
文摘Because of the special underwater environment, many sensors used well in robots working in space or on the land can not be used in the underwater. So an optical fiber type slide tactile sensor is designed by the inner modulation mechanism of the intensity type optical fiber. The principle and structure of the sensor are introduced in detail. The static and dynamic characteristics are analyzed theoretically and experimentally. The dynamic characteristic model is built and the simulation is made by using genetic algorithm based on neural network. In order to use the sensor perfectly, the recognition model of the sensor is built on the basis of the principle of “inverse solution” using neural networks. The control precision and sensitivity of the manipulator are improved.
