Robot of estimating direction based on vanishing point of low luminance image and method estimating thereof
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robots struggle to accurately estimate their orientation in low-luminance environments, as existing methods require external marks and sufficient luminance to operate effectively, making it difficult to identify location and orientation in spaces with transient populations and varying light conditions.
Innovation Solution
A robot equipped with a camera unit and image processor that captures images using histogram equalization and a rolling guidance filter to extract line segments, calculate a vanishing point, and estimate the global angle, enabling orientation estimation even in low-luminance conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external marks are used for location and orientation identification, then the robot can accurately determine its position, but it requires marks to be attached in advance and external hindrances to be removed which is difficult in spaces with transient population
Solution Approach 1:
The patent extracts the location identification function from dependency on external marks and relocates it to natural architectural features (walls, ceilings, floors) that inherently exist in the environment. The vanishing point extraction algorithm identifies orientation based on line segments from these natural structures rather than requiring attached markers.
Solution Approach 2:
The patent makes the location identification system universal by enabling it to work with any architectural structure that has linear features (walls, ceilings, floors) without requiring specific mark attachments. The system adapts to different environments (offices, homes, public spaces) using the same vanishing point-based approach.
2Measurement precision
If camera-based location identification is used, then the robot can determine its position, but luminance must be at a certain level or higher which fails in low-luminance environments
Solution Approach 1:
The patent changes the parameter of image processing by applying histogram equalization to enhance contrast in low-luminance images. This transformation modifies the luminance distribution to make line segments detectable even when original image brightness is insufficient, enabling vanishing point extraction in dark environments.
Solution Approach 2:
The patent replaces the mechanical requirement of sufficient physical light illumination with a computational approach using histogram equalization and edge detection algorithms. Instead of relying on environmental light conditions, the system uses image processing to extract structural information from low-luminance images.
3Reliability
If marks are attached in advance for robot navigation, then accurate orientation can be achieved, but it is not feasible in every space especially those with transient population
Solution Approach 1:
The patent enables the environment to serve itself for navigation purposes by using existing architectural structures (walls, ceilings, floors) as the reference framework. The system extracts vanishing points from these natural structures, making the environment self-describing for robot localization without requiring external mark attachments.
Solution Approach 2:
Instead of attaching marks to the environment and having the robot detect them, the patent inverts the approach by having the robot detect and interpret the existing architectural structures directly. The reference frame is inverted from artificial markers to natural architectural geometry.
Data Source
AI summary
The present invention relates to a robot and method for estimating an orientation on the basis of a vanishing point in a low-luminance image, and the robot for estimating an orientation on the basis of a vanishing point in a low-luminance image according to an embodiment of the present invention includes a camera unit configured to capture an image of at least one of a forward area and an upward area of the robot and an image processor configured to extract line segments from a first image captured by the camera unit by applying histogram equalization and a rolling guidance filter to the first image, calculate a vanishing point on the basis of the line segments, and estimate a global angle of the robot corresponding to the vanishing point.