3D ToF Camera Calibration for Safety-Rated Depth Sensing
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Solution Overview
Problem
Existing 3D depth-sensing technologies, such as 3D ToF cameras, are not safety-rated and cannot be used in safety-critical applications like machine guarding or collaborative robotics due to the lack of compliance with industry-recognized safety standards and robustness in handling complex, rich data.
Innovation Solution
Implementing a system with 3D ToF cameras that includes sensor-specific calibration data stored in a boot file, temperature correction, and error detection mechanisms to ensure compliance with safety standards and handle complex data effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D ToF cameras are used in safety-critical applications, then depth sensing capability is improved, but reliability deteriorates due to lack of safety standard compliance
Solution Approach 1:
The patent applies preliminary action by performing calibration of the 3D ToF camera before deployment in safety-critical applications. The calibration process includes capturing images of calibration targets at multiple positions and orientations, computing intrinsic parameters (focal length, principal point, distortion coefficients), and storing these parameters in non-volatile memory. This preliminary calibration ensures that the camera meets safety standard requirements before actual operation, thereby improving reliability while maintaining depth measurement precision.
2Reliability
If calibration data is stored in non-volatile memory, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies copying by creating a digital copy of calibration data and storing it in non-volatile memory (such as EEPROM or flash memory) within the camera module. Instead of relying on volatile memory that would be lost during power cycles, the calibration parameters are copied to persistent storage. This ensures that the calibration data remains available across power cycles without requiring complex external calibration systems, thereby improving reliability while minimizing the increase in device complexity.
3Measurement precision
If temperature correction is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies parameter changes by implementing temperature compensation for the calibration parameters. The system includes temperature sensors that continuously monitor the operating temperature, and the calibration data is adjusted based on temperature variations. Correction tables or mathematical models are used to modify the intrinsic parameters (focal length, principal point, distortion coefficients) according to temperature changes. This ensures that measurement precision is maintained across different temperature conditions while keeping the correction mechanism integrated within the existing camera system.
4Measurement precision
If multiple calibration targets are used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent applies preliminary action by performing calibration during the manufacturing process or initial setup, and then storing the calibration data in non-volatile memory for use during normal operation. The calibration process involves capturing images of multiple calibration targets at different positions and orientations, computing the intrinsic parameters, and saving the results. Once calibrated, the system can operate without repeated calibration time, thereby improving measurement precision while minimizing time loss during actual application.
Solution Approach 2:
The patent applies self-service by implementing automatic calibration verification and maintenance capabilities. The system can autonomously verify calibration status by capturing images of calibration targets and comparing them against expected patterns. If drift or degradation is detected, the system can automatically re-calibrate without manual intervention. This self-service approach maintains high measurement precision while reducing the time loss associated with manual calibration procedures during operation.
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
The system provides reliable and safe operation by ensuring accurate depth measurements and compliance with safety standards, enabling effective control of machinery in industrial environments.
Implementation Method 1
3D time-of-flight cameras
Implementation Method 2
an image sensor responsive to the same wavelength range
Data Source
AI summary
Systems and methods utilize one or more 3D cameras (e.g., ToF cameras) in industrial safety applications. The 3D camera generates a depth map that may be used by external hardware and software to classify objects in a workcell and generate control signals for machinery. To facilitate sensor-specific calibration and coordination among sensors in a workcell, the sensors may store calibration data in a boot file that is loaded upon start-up. During initialization, the calibration data is loaded and, as the sensor operates, corrections are made to sensed data (e.g., pixel depth values) using the calibration data.