Extrinsic Calibration of 3D Sensors Using Static Target Optimization
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Solution Overview
Problem
Existing extrinsic calibration methods for three-dimensional data acquisition systems require precise positioning of calibration targets, limiting flexibility and speed, and automatic methods necessitate sensor movement, which is impractical.
Innovation Solution
A method using a set of static targets arranged on a calibration plane, comprising at least three non-collinear targets aligned along specific axes, to estimate geometric transformation between the sensor and world frames through cost functions, minimizing errors in roll, pitch, and vertical translation, followed by yaw, longitudinal, and transverse translation estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If precise positioning constraints are imposed on calibration targets, then measurement precision is improved, but device complexity and ease of operation deteriorate
Solution Approach 1:
The calibration method enables self-service by allowing the system to automatically determine target positions and compute extrinsic parameters without requiring manual precise positioning or complex setup procedures. The cost function minimization approach allows the system to self-calibrate using naturally positioned targets.
Solution Approach 2:
The invention changes the parameter representation from fixed precise coordinates to parameters optimized through cost function minimization. By formulating the calibration as an optimization problem, the system can achieve high precision through iterative parameter adjustment rather than relying on mechanically precise target placement.
2Productivity
If automatic extrinsic calibration methods are used, then productivity is improved, but device complexity worsens due to requirement of sensor movement
Solution Approach 1:
Instead of moving the sensor to achieve calibration (conventional approach), the invention inverts the approach by keeping the sensor static and moving the targets to different positions. The extrinsic parameters are then computed from multiple static observations of targets at different locations, eliminating the need for sensor movement mechanisms.
Solution Approach 2:
The calibration process is segmented into multiple independent steps: initial target location determination, cost function formulation, and iterative minimization. This segmentation allows each step to be performed independently using simple equipment, avoiding the need for complex integrated sensor movement systems.
Data Source
AI summary
An extrinsic geometric calibration method for a system for acquiring three-dimensional data including at least one sensor for taking three-dimensional measurements that is associated with a sensor frame, which method aims to define the geometric transformation between the sensor frame and a world frame, by a set of static targets. The method includes an initial step of locating the targets, which aims to determine the coordinates of the targets in the sensor frame by the sensor for taking three-dimensional measurements, a first step of estimating the roll, the pitch and the vertical translation by minimizing a first cost function based on the geometric characteristic of arrangement of the targets on the calibration plane, and a second step of estimating the yaw, the longitudinal translation and the transverse translation by minimizing a plurality of second cost functions based on the geometric characteristic of alignment of the targets in the world frame.