Movable Camera Robot Control for Multi-Area Position Recognition
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Solution Overview
Problem
Existing fixed-camera and on-hand-camera robot control systems require multiple cameras for each work area and suffer from increased cycle times when performing operations on target objects across multiple work areas.
Innovation Solution
A robot control system with a movable camera that captures images of target objects in multiple work areas and an object recognition unit that calculates positional deviations to accurately recognize object positions, allowing a single camera to operate across multiple work areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed camera is attached to each work area, then object position recognition accuracy is maintained, but the number of cameras increases and system complexity increases
Solution Approach 1:
A single movable camera is designed to perform the function of multiple fixed cameras by moving to different predetermined positions corresponding to different work areas. The camera captures images at each position, and the object recognition unit processes these images to recognize object positions across all work areas, making one camera universal for multiple locations.
Solution Approach 2:
The camera is transformed from a static fixed installation to a dynamic movable system. The movable camera can change its position to predetermined locations corresponding to different work areas, enabling it to capture images dynamically at each position. This dynamic positioning allows a single camera to replace multiple fixed cameras while maintaining recognition accuracy.
2Productivity
If multiple cameras are used for multiple work areas, then all work areas can be monitored simultaneously, but cycle time increases due to sequential processing
Solution Approach 1:
Predetermined positions for the movable camera are pre-established corresponding to each work area. The camera moves to these predetermined positions to capture images, and the object recognition unit processes images from multiple positions in parallel. This preliminary setup of positions and parallel processing capability reduces cycle time compared to sequential processing with multiple fixed cameras.
3Device complexity
If a movable camera is used to reduce the number of cameras, then device complexity decreases, but measurement precision may deteriorate due to position deviations
Solution Approach 1:
The object recognition unit calculates the deviation amount of the movable camera from each predetermined position based on captured images. This deviation information is fed back to correct the recognition results, compensating for positioning errors. The feedback mechanism ensures that even with position deviations, the object position recognition accuracy is maintained across all work areas.
4Loss of time
If fixed cameras are installed in each work area, then object recognition can proceed in parallel across all areas, but the cost and system complexity increase
Solution Approach 1:
Multiple fixed cameras across different work areas are merged into a single movable camera system. The movable camera visits predetermined positions corresponding to each work area and captures images sequentially, while the object recognition unit processes these images in parallel. This merging reduces the total number of cameras from multiple to one, while maintaining parallel processing capability through coordinated movement and processing.
Data Source
AI summary
In a robot control system, a robot performs an operation on a target object in each of work areas. A movable camera respectively captures images of the target object in the work areas. An object recognition unit recognizes a position of an object based on an image captured from a predetermined position. A movable camera acquires a predetermined image captured to include a reference object serving as a positional reference and the target object in a field of view. The object recognition unit registers a position of the reference object recognized based on an image captured from the predetermined position as a reference position in advance, calculates a deviation amount of a position of the movable camera from the predetermined position based on the reference position and the position of the reference object, and recognizes a position of the target object based on the deviation amount and the predetermined image.