Method for extracting outer space feature information

Abstract

A method is provided for extracting outer space feature information from spatial geometric data. The method comprises: an input step of inputting spatial geometric data for a target region; a sampling step of determining a sample by selecting an arbitrary area for the spatial geometric data input in the input step using a preset selection method; a feature extraction step of acquiring feature information for a corresponding sampling plane using a convex hull method based on sampling information including sampling plane information of the spatial geometric data for a sampling plane selected in the sampling step. The sampling step and the feature extraction step are repeatedly performed in a preset manner.

Description

technical field [0001] The present invention is a technique for obtaining feature information from spatial geometric information of an object region. Background technique [0002] Unlike in the past when the demand was mainly concentrated on stationary robots for industrial use, at present, with the increasing demand in the home robot market, research on mobile robots is being actively carried out. [0003] Various studies have been conducted on how to improve the performance of mobile robots, and one of such core research technologies is the technology of finding features in space. For example, in real life, in order for a robot to move or recognize an object, the robot must have the technology to find features. For this, it is necessary to be able to extract appropriate features from the information observed by various sensor information. [0004] In particular, unlike factories where industrial stationary robots exist, in spaces where people move, various environmental ...

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Problems solved by technology

[0007] However, conventional technologies such as position estimation and object recognition were implemented in a static environment. Therefore, the above technologies can only be realized in an environment completely different from the actual environmental conditions, which include potential dynamic elements or dynamics with objects or dynamics. elements

That is, a static environment containing only structures is assumed to be an extracted feature that is fixed within the environment or exists under controlled movement. Therefore, under dynamic environmental conditions, the presence of uncontrolled objects or people is not predictive. Therefore, there is a problem that it is difficult to directly apply conventional position estimation and object recognition technologies to dynamic environments similar to the actual environment.

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