Robot Vision Control via Coordinate Transformation
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Solution Overview
Problem
Existing robot vision systems face accuracy and cost issues due to vibration and deformation of the camera stand, leading to frequent recalibration needs and increased complexity in environments with disturbances.
Innovation Solution
A method involving a fixed camera and reference markers, where a measuring device attached to the robot calculates the relative positional relationship between the workpiece and the robot using images captured by both the fixed camera and the hand camera, allowing for high-accuracy control with reduced hardware and cost.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the stiffness of the camera stand is increased to prevent vibration and deformation, then the position stability of the vision sensor is improved, but the hardware size and manufacturing cost increase
Solution Approach 1:
The patent replaces the mechanical solution (stiff camera stand) with a computational solution (coordinate transformation). Instead of physically preventing vibration through structural stiffness, the system mathematically transforms coordinates between the vision sensor coordinate system and robot coordinate system, eliminating the need for a rigid mechanical support structure.
Solution Approach 2:
The patent changes the approach from physical parameter optimization (stiffness) to coordinate system parameter transformation. By introducing transformation parameters between coordinate systems, the system achieves position accuracy without requiring changes to the physical stiffness of the camera stand.
2Manufacturing precision
If the camera stand is made more rigid to maintain calibration accuracy, then the manufacturing precision is improved, but the cost and hardware complexity increase
Solution Approach 1:
The patent substitutes mechanical rigidity requirements with computational coordinate transformation. The calibration accuracy is maintained through mathematical transformation between coordinate systems rather than through expensive rigid mechanical structures, simplifying manufacturing and reducing costs.
3Measurement precision
If frequent recalibration is performed to maintain accuracy in vibrating environments, then the measurement precision is improved, but the productivity decreases
Solution Approach 1:
The patent performs coordinate transformation calibration in advance and stores the transformation parameters. This preliminary calibration eliminates the need for frequent recalibration during robot operations, maintaining measurement precision while avoiding interruptions to productivity.
Solution Approach 2:
The system uses the stored transformation parameters to continuously correct position and orientation measurements without requiring active recalibration. This feedback mechanism maintains accuracy throughout operation without stopping the robot for recalibration.
4Stability of the object's composition
If a complex camera stand structure is used to prevent vibration, then the stability is improved, but the device complexity increases
Solution Approach 1:
The patent replaces complex mechanical stabilization structures with a computational coordinate transformation system. The stability is achieved through mathematical correction rather than mechanical design, significantly simplifying the camera stand structure.
Data Source
AI summary
A method of controlling a robot system includes measuring, capturing, and calculating. A measuring device attached to the robot measures a position and an orientation of a marker with respect to the robot. An imaging device captures an image of the marker and a workpiece. A control device calculates a relative positional relationship between the workpiece and the robot in accordance with a result obtained by the measuring device and with the image captured by the imaging device.