Sensor Registration via Calibration Target Planar Surface
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Solution Overview
Problem
Existing sensor arrangements for object recognition in monitored zones using multiple distance-measuring sensors face challenges in automated registration, requiring laborious additional measures and in-depth technical knowledge due to noise in measured data, which complicates precise orientation and position determination of calibration targets.
Innovation Solution
An automatic registration method using a calibration target with a planar surface, where the position is determined from multiple poses and the orientation is derived from connection lines between target positions, allowing for a robust and user-friendly registration process that reduces noise-induced errors, enabling precise fusion of sensor data without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple distance-measuring sensors are used to monitor the entire zone, then the coverage area is improved, but the registration complexity increases due to noise in measured data
Solution Approach 1:
A calibration target with planar surface serves as an intermediary object between multiple sensors. The target provides measurable geometric features (planar surface position and orientation) that mediate the registration process, transforming the complex direct sensor-to-sensor calibration into a simpler sensor-to-target-to-sensor indirect process that is more robust against measurement noise
Solution Approach 2:
The patent replaces manual, interactive registration processes with an automatic computational method. The registration is achieved through automated detection of the calibration target by each sensor and automatic calculation of transformation instructions, eliminating the need for manual target positioning and interactive coordinate system alignment
2Measurement precision
If manual registration measures are taken to achieve precise sensor alignment, then the measurement precision is improved, but the ease of operation deteriorates due to laborious procedures
Solution Approach 1:
The calibration target and sensors perform self-calibration through automatic detection and computation. Each sensor automatically detects the calibration target in its own coordinate system, and the control unit automatically calculates the transformation instructions without requiring manual intervention or expert knowledge, making the system self-sufficient and easy to operate
Solution Approach 2:
The calibration target is designed with a planar surface that can be detected by multiple sensors simultaneously. By preparing this standardized geometric reference object in advance, the system enables automatic preliminary alignment and registration before actual measurement operations begin, simplifying the overall process
3Reliability
If additional calibration measures are implemented to reduce noise effects, then the reliability is improved, but the device complexity increases
Solution Approach 1:
The patent uses the full geometric information (both position and orientation) of the calibration target's planar surface, rather than attempting to use only partial information. By leveraging all available measurements from the planar surface detection, the system achieves robust noise reduction through excessive use of measurement data, improving reliability without adding complex hardware
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
This method enables precise registration of multiple sensors with minimal steps, satisfying technical safety standards, and provides a clear specification for the fused sensor system, ensuring accurate transformation and expanded field of view while being easy to integrate into existing configurations.
Implementation Method 1
the laser scanner measures the transit time until a transmitted light pulse is received again
Implementation Method 2
The light is remitted at objects in the monitored zone and is evaluated in the scanner
Data Source
AI summary
A sensor arrangement for object recognition in a monitored zone is provided having a first and second distance-measuring optoelectronic sensor whose fields of vision overlap, and having a common control unit which is formed for determining a position of a calibration target in the overlap region with respect to the first and second sensor to determine a transformation instruction between coordinate systems of the sensors in a registration mode so that measured points of the sensors can be combined in a common global coordinate system. The common control unit is designed to determine positions of the calibration target with respect to the first and second sensor and to determine that transformation instruction which brings a connection line between the positions with respect to the first sensor's coordinate system to cover the connection line between the positions with respect to second sensor's coordinate system.