Robot Obstacle Recognition Method Based on Gradient Histogram and Support Vector Machine

Abstract

The invention discloses a robot obstacle recognition method based on gradient histogram and support vector machine. The method mainly includes two parts: first, in the feature extraction stage, the feature of the transmission line obstacle of the principal component gradient histogram is proposed extraction algorithm. Utilizing the characteristics of typical obstacles with different structural compositions and spatial layouts, by calculating the statistical characteristics of common online obstacles and using the feature extraction of the HOG algorithm, feature points that are independent of illumination and scale changes can be obtained, which can effectively remove interference. At the same time, the principal component analysis is used to further reduce the dimensionality of the obtained eigenvectors to obtain the principal component gradient histogram, which can effectively reduce irrelevant features, reduce the amount of calculation, and use the least amount of features to establish a feature set corresponding to obstacles. One-step target identification provides good support. Second, in the stage of target recognition, a linear support vector machine (SVM) is used for recognition, and a very good recognition effect is obtained.

Description

technical field [0001] The invention relates to a robot obstacle recognition method based on a gradient histogram and a support vector machine. Background technique [0002] The autonomous navigation system of transmission line inspection robots has always been one of the research hotspots in smart grid maintenance and safety monitoring. It has broad application prospects in the fields of transmission line inspection, maintenance, rapid fault location, and online monitoring. However, when the line inspection robot uses a wheeled walking mechanism to "crawl" along the overhead transmission line, the anti-vibration hammers, insulators, suspension line clamps, tension line clamps and other pole support accessories installed on the wires block the progress of the line inspection robot. At the same time, different obstacles have relatively obvious changes in posture and angle of view, coupled with complex field inspection scene backgrounds, large-scale changes in lighting angles,...

AI Technical Summary

Problems solved by technology

However, when the line inspection robot uses a wheeled walking mechanism to "crawl" along the overhead transmission line, the tower support accessories installed on the wires such as shockproof hammers, insulators, suspension line clamps, and tension line clamps block the progress of the line inspection robot.

At the same time, different obstacles have relatively obvious changes in posture and angle of view, coupled with complex field inspection scene backgrounds, large-scale changes in lighting angles, and shaking of the visual system itself, the problem of robust online object recognition has always been is a challenging research topic

However, the defect of existing statistical techniques is that under the influence of large-scale complex background and illumination, there will inevitably be a large number of false detection results, so the reliability and validity cannot be guaranteed.

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