Control method of capacitive touch handle based on multi-sensing system

Abstract

The invention relates to a control method of a capacitive touch handle based on a multi-sensing system, which is characterized in that the touch handle is wrapped with a capacitor array flexible pressure sensor, a tension and compression sensor is arranged at one end of the touch handle along the length direction of the handle, and an inertial measurement unit (IMU) is arranged in the touch handle; the method comprises the following specific steps: acquiring a displacement signal acquired by a tension-compression sensor, detecting stress change along the vertical direction of a handle, and simultaneously acquiring linear accelerations and rotation angular rates of the handle from three directions, which are measured by an inertial measurement unit (IMU); obtaining a grabbing image when a human hand grabs the touch handle, and processing the grabbing image; and determining a holding intention by using a convolutional neural network model, and carrying out multi-perception information fusion. The method is suitable for collecting human hand grabbing information in contact type man-machine cooperation, the human hand posture can be estimated in real time, and the intention of an operator can be accurately judged.

Description

technical field [0001] The invention relates to the fields of information collection and processing, machine learning, screen printing, etc., and in particular relates to a control method for a capacitive tactile handle based on a multi-sensory system. Background technique [0002] In recent years, human-computer collaboration has become one of the most popular research directions in the field of robotics, and the basis and premise of realizing human-computer interaction is to perceive and extract the operator's intention as comprehensively as possible in human-computer collaboration. Humans can perceive information about the surrounding environment through vision, hearing, and touch / force. At present, the development of machine hearing and vision has been relatively mature, but there is little research on the acquisition of touch / force information that operators rely on for grasping. The grasping intention detection of the current technology is mainly through the six-dimens...

AI Technical Summary

Problems solved by technology

Humans can perceive information about the surrounding environment through vision, hearing, and touch / force. At present, the development of machine hearing and vision has been relatively mature, but there is little research on the acquisition of touch / force information that operators rely on for grasping. The grasping intention detection of China mainly uses six-dimensional force sensors, but the price is expensive, the operation is inconvenient, and the relevant grasping information detected is also lacking. The traditional tactile data gloves have complex structure, difficult production, cumbersome wearing, and high cost.

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