Mobile Robot Position Estimation from Split Structure Image Panoramas
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Solution Overview
Problem
Existing self-position estimation techniques for mobile robots require pre-created landmark maps and specialized imaging equipment, limiting their ability to estimate position without additional imaging purposes and equipment beyond their primary work function.
Innovation Solution
A self-position estimation device that uses split imaging and panorama composition to estimate the position of a camera-equipped mobile robot without the need for landmarks or specialized imaging equipment, by acquiring and processing structure images to generate a panorama composite image and calculate relative and absolute position coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a landmark map is created in advance and landmarks are tracked for self-position estimation, then the robot can estimate its position, but the robot needs to constantly track landmarks and may miss them, making estimation impossible
Solution Approach 1:
The invention extracts the self-position estimation function from the landmark tracking system. Instead of relying on pre-defined landmarks, the system uses the robot's own movement information and captured images to estimate position, removing the dependency on external landmark markers that may be missed or unavailable.
Solution Approach 2:
The imaging device serves multiple functions: it captures images for both the primary work purpose (e.g., structure inspection) and simultaneously provides data for self-position estimation. This eliminates the need for specialized imaging equipment dedicated solely to position estimation, making the system more versatile and reliable.
2Measurement precision
If imaging for creating a landmark map is performed, then self-position estimation can be achieved, but imaging different from the work purpose (e.g., structure inspection) is required
Solution Approach 1:
The system uses the same imaging device and captured images for both the primary work purpose (structure inspection) and self-position estimation. The captured images contain sufficient information for both inspection tasks and position calculation, eliminating the need for separate imaging systems or specialized equipment.
Solution Approach 2:
The invention merges the self-position estimation function with the primary work imaging process. By combining position estimation calculations with the existing image processing workflow, the system achieves position awareness without adding separate imaging hardware or complex dedicated imaging procedures.
3Measurement precision
If omni-directional images are captured at the initial position and a super-wide angle lens is mounted, then self-position estimation can be performed, but special imaging equipment is needed
Solution Approach 1:
The system achieves self-position estimation using a standard camera with its normal field of view, rather than requiring super-wide angle lenses or omni-directional cameras. The position estimation is performed by analyzing the robot's movement and comparing captured images with a pre-acquired image of the same location, using the same imaging device for both purposes.
4Measurement precision
If the robot moves to capture images for self-position estimation, then position data can be obtained, but movement other than the work purpose is required
Solution Approach 1:
The system extracts position information from images captured during normal work movements, rather than requiring dedicated movement for position estimation. The robot uses its own movement data and the images captured during inspection tasks to calculate position, removing the need for separate position-sampling movements.
Solution Approach 2:
The robot performs self-position estimation using its own captured images and movement information without requiring external guidance or dedicated positioning movements. The system serves itself by utilizing the data already collected during its primary inspection work to determine its location.
Data Source
AI summary
Disclosed are a self position estimation device, a self position estimation method, a program, and an image processing device that suppress imaging and movement other than a work purpose of a robot, do not need a landmark, and do not need special imaging equipment for application of the robot other than the work purpose. A self position estimation device (400) includes a first structure image acquisition unit (401) that acquires a plurality of structure images including a first structure image and a second structure image, a panorama composition unit (403) that generates a panorama composite image by subjecting the plurality of structure images including the first structure image and the second structure image to panorama composition, a first image coordinate acquisition unit (405) that acquires second image coordinates as coordinates of a specific position of the second structure image, and a first relative position coordinate calculation unit (407) that calculates relative position coordinates as relative actual coordinates of a second position as a relative self position using a transformation coefficient for transformation from an image coordinate system to an actual coordinate system.