Mobile Robot Interference Region Setting via 2D Camera
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Solution Overview
Problem
Existing methods for setting interference regions for mobile robots are cumbersome and costly, requiring manual resetting each time the robot is moved, and rely on expensive 3D cameras for accurate positioning and orientation of obstructions.
Innovation Solution
An interference region setting apparatus that uses a shape model storage section, position and orientation calculation section, and interference region setting section to automatically set and display the interference region in the robot coordinate system, utilizing a 2D camera for cost-effectiveness and precision, with features like shape model storage, image analysis, and coordinate conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual resetting of interference region is performed each time the robot is moved, then the interference region can be accurately set, but the operation becomes cumbersome and time-consuming
Solution Approach 1:
The system performs preliminary actions by capturing images of the work environment before the robot moves, pre-calculating the interference region based on the captured image data. When the robot moves to a new position, the pre-calculated interference region data can be quickly retrieved and adjusted rather than performing full manual resetting, thus maintaining accuracy while reducing time loss.
2Measurement precision
If expensive 3D cameras are used for accurate positioning and orientation of obstructions, then the interference region can be precisely determined, but the system cost increases
Solution Approach 1:
Instead of using expensive 3D cameras to directly capture three-dimensional spatial information, the system uses a 2D camera to capture images of the work environment and then processes these 2D images through image processing algorithms to extract position and orientation data of obstructions. This copying approach of using 2D image data to represent 3D spatial relationships achieves the required measurement precision while significantly reducing system cost.
Solution Approach 2:
The patent replaces the mechanical/optical 3D measurement system (3D camera) with an image processing system that uses 2D camera images. By substituting the direct 3D sensing mechanism with computational image analysis, the system achieves comparable positioning accuracy without the high cost of specialized 3D imaging hardware.
3Ease of operation
If automatic interference region setting is implemented using 2D camera and image processing, then the operation becomes simpler and costs are reduced, but the measurement precision may be compromised
Solution Approach 1:
The patent replaces complex manual measurement and calculation operations with automated image processing algorithms. The system captures images using a 2D camera and automatically extracts obstruction position, orientation, and dimensions through computer vision techniques, then calculates the interference region without manual intervention. This substitution maintains high measurement precision while significantly improving ease of operation.
Solution Approach 2:
The system performs self-service by automatically capturing images of the work environment, processing the images to identify obstructions, calculating the interference region, and updating the robot control system without requiring manual operation. The robot autonomously determines its own interference regions based on image processing results, eliminating the need for manual setup while maintaining accuracy.
Data Source
AI summary
An interference region setting apparatus capable of setting an interference region in a coordinate system of a mobile robot, with an inexpensive configuration and a little effort. The apparatus has: a shape model storage section configured to store a shape, a position, and an orientation of an obstruction present in a work region of the mobile robot as an obstruction shape model, in a reference coordinate system; a position and orientation calculation section configured to analyze an image, captured by the image capturing apparatus, of a shape feature in a fixed position within the work region, and calculate a position and orientation of the reference coordinate system represented in a robot coordinate system; and an interference region setting section configured to set an interference region based on the position and orientation of the reference coordinate system converted into the robot coordinate system and the stored obstruction shape model.