Onboard Sensor Alignment Using Parallel Calibration Threads
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Solution Overview
Problem
Existing sensor calibration methods are time-consuming and require manual adjustment at service locations, failing to adapt to changes in sensor position due to manufacturing tolerances or environmental factors, leading to inaccurate measurements.
Innovation Solution
A computer-implemented method using parallel computing and memory management to dynamically calibrate sensors on a vehicle by initiating multiple threads for data parsing, storage, and alignment transformation, optimizing computational efficiency for real-time adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration at service locations is used, then sensor alignment accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs self-calibration using an onboard processor that automatically computes alignment transformations between sensor coordinate systems and vehicle coordinate systems. The processor receives sensor data, determines transformation matrices, and applies corrections without requiring external service location intervention, enabling the sensor system to calibrate itself in real-time
Solution Approach 2:
The system pre-computes alignment transformations and stores them in memory for rapid application. By preparing transformation matrices in advance and maintaining them in ready-to-use format, the system eliminates the need for time-consuming manual calibration procedures when alignment adjustments are needed
2Measurement precision
If manual calibration at service locations is used, then sensor alignment accuracy is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The calibration system operates autonomously using onboard computing resources. The processor automatically receives sensor data, computes alignment transformations, and applies corrections without requiring operator intervention or specialized service location equipment, making the system easy to operate
Solution Approach 2:
The system replaces manual mechanical calibration procedures with automated computational methods. Instead of physical adjustment mechanisms requiring technician intervention, the system uses software-based coordinate transformation algorithms to achieve precise sensor alignment, significantly simplifying operation
3Productivity
If parallel thread processing is implemented, then computational efficiency is improved, but system complexity increases
Solution Approach 1:
The computational workload is divided into separate parallel threads, each handling specific aspects of sensor data processing and alignment computation. This segmentation enables simultaneous execution of multiple processing tasks on multi-core processors, improving overall computational efficiency while organizing complexity into manageable modular units
Data Source
AI summary
A computer-implemented method for aligning a sensor to reference coordinate system includes initiating a plurality of threads, each thread executes simultaneously and independent of each other. A first thread parses data received from the sensor and stores the parsed data in a data buffer. A second thread computes an alignment transformation using the parsed data to determine alignment between the sensor and the reference coordinate system. The computing includes checking that the data buffer contains at least predetermined amount of data. If at least the predetermined amount of data exists, an intermediate result is computed using the parsed data in the data buffer; otherwise, the second thread waits for the first thread to add more data to the data buffer. The second thread outputs the intermediate result into the data buffer. A third thread outputs the alignment transformation, in response to completion of alignment computations.