Sensor Offset Calibration via Velocity Vector Iteration
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Solution Overview
Problem
Multi-view triangulation systems face accuracy and efficiency issues due to the need for extensive calibration and rigidity requirements, limiting their scalability and deployment in dynamic environments, as they require external calibration targets and are prone to operational downtime.
Innovation Solution
A real-time calibration system that continuously adjusts depth estimation algorithms for the relative positions and orientations of light sensors, allowing for flexible mounting and wider deployment by iteratively reducing velocity vectors to minimize mismatches and maintain accurate extrinsic calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive calibration target structures are used for calibration, then measurement precision is improved, but loss of time increases due to non-operational downtime
Solution Approach 1:
The system performs preliminary calibration by embedding identification markers in the scene environment beforehand, eliminating the need for separate calibration sessions. The markers are pre-positioned and the system learns their locations during normal operation, so calibration data is collected in advance rather than requiring dedicated calibration time.
Solution Approach 2:
The calibration system uses the scene itself and naturally present features as calibration targets, allowing the system to calibrate itself during normal operation without external intervention. The identification markers serve as self-contained calibration references that the system can autonomously detect and use for continuous calibration.
2Measurement precision
If rigid mounting structures with large base offsets are used, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical rigid mounting structures with a computational calibration approach. Instead of relying on physically rigid assemblies to maintain precise sensor relationships, the system uses software-based calibration that continuously computes and corrects for positional and orientational drift, substituting mechanical rigidity with algorithmic compensation.
Solution Approach 2:
The calibration system dynamically adjusts extrinsic parameters (sensor positions and orientations) based on real-time detection of identification markers. Rather than fixing these parameters mechanically, the system continuously updates them through computational optimization, allowing flexible mounting while maintaining accuracy.
3Measurement precision
If frequent re-calibration is performed to maintain accuracy, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The calibration process becomes continuous rather than periodic. The system continuously detects identification markers during normal operation and continuously updates calibration parameters, making calibration an ongoing background process rather than a separate operational step. This eliminates interruptions and maintains productivity while ensuring continuous accuracy.
Solution Approach 2:
The system performs calibration data collection during normal operational periods rather than requiring separate calibration sessions. By gathering calibration information continuously as the system operates, calibration and productive work occur simultaneously, eliminating the need to stop operations for recalibration.
4Manufacturing precision
If elaborate 3D rigging of sensor assemblies is performed, then manufacturing precision is improved, but loss of time increases during assembly and deployment
Solution Approach 1:
The system transitions from fixed manufacturing precision requirements to dynamic parameter adjustment. Instead of requiring precise assembly during manufacturing, the system allows flexible mounting and then computationally determines and adjusts the actual sensor positions and orientations through calibration, shifting the precision requirement from assembly to software configuration.
Solution Approach 2:
Complex mechanical 3D rigging and precise physical assembly are replaced with computational calibration. The system uses software to determine and correct positional relationships rather than relying on precision mechanical assembly, eliminating time-consuming rigging processes while maintaining accuracy.
Data Source
AI summary
Embodiments are directed to calibrating multi-view triangulation systems that perceive surfaces and objects based on reflections of one or more scanned laser beams that are continuously sensed by two or more sensors. In addition to sampling and triangulating points from a spline formed by an unbroken line trajectory of a laser beam, the calibration system samples and triangulates a corresponding velocity vector. Iterative reduction is performed on velocity vectors instead of points or splines. The velocity vector includes directions and magnitudes along a trajectory of a scanning laser beam which are used to determine the actual velocities. Translation and rotation vectors are based on the velocity vectors for matching trajectories determined for two or more sensors having offset physical positions, which are used to calibrate sensor offset errors associated with the matching trajectories provided to a modeling engine.