Satellite Docking Fiducial Tracking for Rapid Pose Calibration
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Solution Overview
Problem
Current robotic workcells require precise and time-consuming calibration processes to determine the position and orientation of fixtures relative to robot arms, which become ineffective if the positions are slightly altered.
Innovation Solution
A system and method that uses a sensor to detect fiducials on robot arms and fixtures, determining their positions and orientations relative to a vehicle's coordinate system, allowing for automatic calibration and simplified setup by mapping coordinate systems without the need for fixed positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precision placement or calibration is used to determine fixture positions relative to robot arms, then positioning accuracy is improved, but setup time and system complexity increase
Solution Approach 1:
The patent replaces mechanical calibration systems with an optical vision system. Cameras capture images of fiducial markers on fixtures and robot arms, and a processor automatically calculates relative positions through image processing and coordinate transformation, eliminating the need for manual precision placement or mechanical calibration procedures
Solution Approach 2:
The system performs automatic self-calibration by capturing images of fiducial markers and computing coordinate transformations without external intervention. The processor automatically determines the position and orientation of fixtures relative to robot arms through algorithmic processing of visual data, making the calibration process self-executing
2Measurement precision
If precision placement or calibration is used to determine fixture positions relative to robot arms, then positioning accuracy is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical calibration systems with a simplified optical vision system. The solution uses standard cameras and fiducial markers instead of precision mechanical fixtures, reducing mechanical complexity while maintaining positioning accuracy through optical measurement and computational geometry
Solution Approach 2:
The vision system serves multiple functions: it captures images for position determination, provides feedback for robot control, and enables coordinate transformation between different reference frames. This multi-functional approach consolidates what would otherwise require separate calibration devices and measurement systems
3Measurement precision
If fiducials are used for tracking and servo control feedback, then positioning accuracy is improved, but the system requires continuous feedback loops increasing complexity
Solution Approach 1:
The patent performs coordinate transformation and position determination in advance, establishing the spatial relationship between fixtures and robot arms before operation begins. This preliminary calibration eliminates the need for continuous feedback loops during operation, as the robot controller can directly use the pre-computed transformation data for positioning
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables rapid and accurate determination of fixture positions relative to robot arms, simplifying the setup process and allowing the workcell to function without requiring fixtures to remain in fixed positions, thus enhancing operational flexibility and efficiency.
Implementation Method 1
a sensor on which is formed an image of a target item that is within a Field of View (FOV) of the sensor
Data Source
AI summary
A system for determining the position and orientation of a satellite relative to an approaching vehicle is disclosed herein. The system includes multiple target items configured to be disposed on the satellite at different locations and a sensor configured to be attached to the vehicle and to provide information about the locations of the target items within the Field of View (FOV) of the sensor. The system also includes a processor and a memory comprising the locations of the plurality of target items on the satellite and instructions that, when loaded into the processor and executed, cause the processor to determine a position and an orientation of the satellite relative to the vehicle.