Robot barrier identification method based on gradient histogram and support vector machine

Abstract

The invention discloses a robot barrier identification method based on a gradient histogram and a support vector machine. The method comprises two parts of a characteristic extraction stage and a target identification stage, for the characteristic extraction stage, a characteristic extraction algorithm of a power transmission line barrier of a principal component gradient histogram is proposed, the characteristic that typical barriers have different structures and space layouts is utilized, statistics characteristics of common online barriers are calculated, characteristic extraction is carried out by utilizing an HOG algorithm, characteristic points irrelevant to illumination and scale change can be acquired, interference can be effectively removed, moreover, dimension reduction operation for acquired characteristic vectors can be realized by utilizing main component analysis to acquire the principal component gradient histogram, irrelevant characteristics can be effectively reduced, operand is reduced, least characteristics are utilized to establish a characteristic set of the corresponding barriers, and excellent support is provided for next target identification; for the target identification stage, the linearity support vector machine is utilized for identification, and the excellent identification effect is acquired.

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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