Touch information classified computing and modelling method based on machine learning

Abstract

The invention relates to a touch information classified computing and modelling method based on machine learning. The method comprises the following steps: acquiring a touch sequence of a training set sample, modelling by adopting a linear dynamic system model, extracting dynamic characteristics of a sub touch sequence, calculating distance of the dynamic characteristics of the sub touch sequence by adopting Martin distance, clustering a Martin matrix by adopting a K-medoids algorithm, constructing a code book, carrying out characterization on each touch sequence by adopting the code book to obtain a system packet model, putting the system packet model of the training set sample and a training set sample label into an extreme learning machine for training a classifier, and putting the system packet model of a to-be-classified sample into the classifier to obtain a label for type of an object. The touch information classified computing and modelling method has the advantages that the actual demand of a robot on stable and complaisant grasping of a non-cooperative target is met, data foundation is provided for completion of a precise operation task, and other sensing results can be fused and computed, so that the description and recognition capability on different targets is enhanced by virtue of multi-source deep perception, and a technical foundation is laid for implementation of intelligent control.

Description

technical field [0001] The invention relates to the field of robot tactile modeling, in particular to a machine learning-based computational modeling method for tactile information classification. Background technique [0002] At present, robots are usually equipped with a variety of sensors to achieve fine operation, but all kinds of sensors generally only use independent application methods for different modal sensors to understand the surrounding environment, cutting off the internal connection between information, so it will seriously reduce the perception of action. The degree of intelligence. In order to accurately provide information such as the state of the operating device itself, the position and attributes of the operating object, it is necessary to study the theory and method of multi-modal fusion of vision and touch, and to analyze the material, deformation, position, and distance of the operating object from different angles. Measurement, thus providing a data...

AI Technical Summary

Problems solved by technology

The establishment of a visual and tactile model first requires the establishment of a tactile model. However, according to patent searches, there is currently no modeling method for classifying and calculating tactile information.

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