Autonomous Docking Pose Detection With Passive Fiducial Markers
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Solution Overview
Problem
Current robotic workcells require precise calibration and operator intervention to determine the position and orientation of equipment, which is time-consuming and inefficient, especially when the robot arm and fixtures do not have fixed locations relative to each other.
Innovation Solution
A system that uses passive camera systems to autonomously determine the location and orientation of items within a workcell by converting information from a camera module's coordinate system to a robot module's coordinate system, allowing the robot arm to interact with items without continuous feedback from the camera module, and embedding necessary information in fixtures for automatic processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precision placement or calibration is used to determine robot arm and fixture positions, then positioning accuracy is improved, but setup time and operational complexity increase
Solution Approach 1:
The system uses fiducial markers placed on fixtures that the robot arm can autonomously detect and use for self-calibration. The robot arm independently determines the positions of fixtures relative to itself without external intervention, enabling automatic positioning and eliminating manual calibration processes.
Solution Approach 2:
The patent replaces manual mechanical calibration processes with an automated vision-based system using fiducial markers. Instead of physically measuring and adjusting positions manually, the system uses image processing and coordinate transformation to automatically determine relative positions, substituting mechanical calibration with computational methods.
2Measurement precision
If manual calibration is performed to establish coordinate systems, then positioning precision is improved, but automation level decreases
Solution Approach 1:
The robot arm autonomously performs coordinate system calibration by detecting fiducial markers on fixtures and automatically computing transformation matrices. The system independently establishes the relationship between its own coordinate system and fixture coordinate systems without human intervention, achieving both precision and full automation.
Solution Approach 2:
The system uses feedback from fiducial marker detection to continuously refine position estimates. The robot arm detects markers, computes coordinate transformations, and uses this information to adjust its positioning and planning, creating a closed-loop autonomous calibration process that maintains both accuracy and automation.
3Measurement precision
If active fiducials with illuminators are used for tracking, then tracking accuracy is improved, but system complexity and cost increase
Solution Approach 1:
The patent uses passive fiducial markers instead of active illuminated fiducials. These passive markers are simple, inexpensive objects that reflect ambient light rather than emitting their own light. This eliminates the need for illuminators, batteries, and complex active components while maintaining sufficient tracking accuracy through the robot arm's vision system.
Solution Approach 2:
The system extracts only the essential fiducial marker function from the more complex active fiducial system. By removing the illumination component and using passive reflective markers, the system achieves the necessary tracking capability with significantly reduced complexity and cost, keeping only what is essential for the application.
Data Source
AI summary
A system for connecting a first ship to a second ship, the system having a plurality of target items coupled to the second ship, a camera module coupled to the first ship and configured to provide information comprising positions of images of the target items in a FOV, and a processor coupled to the camera module and a memory and configured to determine a first position and a first orientation of the second ship relative to the first ship.