Extrinsic Sensor Calibration for Multi-Sensor Docking Assist
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Solution Overview
Problem
Conventional automated directional control systems for vehicles face challenges in accurate calibration and retrofitting, leading to unreliable docking or parking assist, especially in crowded conditions and with external disturbances like wind or water currents.
Innovation Solution
A sensor calibration system that includes a logic device, memory, sensors, actuators, and modules to interface with sensors and actuators, which determines calibration transformations to link sensor data from multiple sensors, enabling accurate docking assist control signals for navigation control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional automated directional control systems use multiple sensors for docking assist, then measurement capability is improved, but calibration complexity and reliability deteriorate due to difficulty in spatial alignment and sensor drift
Solution Approach 1:
The patent introduces an intermediary calibration transformation process that mediates between multiple sensors and the navigation control system. This intermediary layer automatically computes spatial relationships and coordinate transformations, eliminating the need for manual calibration while maintaining measurement precision across multiple sensors.
Solution Approach 2:
The system performs self-calibration by automatically determining calibration transformations using sensor data and pose measurements without requiring direct user input. The logic device continuously computes calibration parameters based on observed sensor relationships, enabling the system to self-correct for drift and displacement over time.
2Adaptability or versatility
If sensors are retrofitted into existing vehicles, then adaptability is improved, but calibration accuracy deteriorates due to difficulty in achieving precise spatial alignment
Solution Approach 1:
The calibration transformation is made dynamic rather than static. The system continuously updates calibration parameters based on real-time sensor data and pose measurements, allowing the calibration to adapt to physical displacements and mounting variations that occur during retrofitting, thereby maintaining accuracy despite imperfect initial alignment.
Solution Approach 2:
The system changes calibration parameters dynamically based on observed sensor behavior and spatial relationships. By adjusting transformation parameters continuously rather than relying on fixed pre-calibration values, the system compensates for mounting variations and achieves accurate spatial alignment even when sensors are retrofitted to existing vehicles.
3Measurement precision
If manual calibration is performed to achieve accurate sensor alignment, then measurement precision is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary automatic calibration computations before navigation operations begin. By pre-computing calibration transformations using initial sensor data and pose measurements, the system eliminates time-consuming manual calibration steps while ensuring measurement precision is achieved before the vehicle begins operation.
Solution Approach 2:
The calibration process is automated and performed without direct user input. The logic device independently computes calibration transformations using sensor data, eliminating the need for manual intervention and significantly reducing calibration time while maintaining or improving accuracy through algorithmic optimization.
4Reliability
If multiple sensors are used to handle environmental disturbances, then reliability is improved, but system complexity and difficulty of calibration increase
Solution Approach 1:
The patent merges multiple sensor inputs and calibration processes into a unified calibration transformation framework. By combining data from multiple sensors and integrating their calibration requirements into a single computational process, the system maintains reliability through multi-sensor input while reducing overall system complexity through consolidation.
Solution Approach 2:
The calibration transformation system serves multiple functions simultaneously: it aligns multiple sensors, compensates for drift, handles physical displacement, and provides coordinate transformations for navigation. This multi-functional approach maintains reliability across diverse operational requirements while avoiding the need for separate calibration systems for each function.
Data Source
AI summary
Techniques are disclosed for systems and methods to provide extrinsic sensor calibration for mobile structures. A sensor calibration system includes first and second sensors coupled to a mobile structure and a logic device. The logic device is configured to receive first and second series of pose measurements corresponding to sensor data provided by the respective first and second sensors, determine a set of intermediate calibration transformation estimates corresponding to the first and second sensors based, at least in part, on a scale-dependent calibration error function and/or the first and second series of pose measurements, and determine an ongoing calibration transformation estimate corresponding to the first and second sensors based, at least in part, on the determined set of intermediate calibration transformation estimates.