Dynamic Sensor Fusion for Autonomous Navigation Calibration
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Solution Overview
Problem
Autonomous navigation systems face challenges in accurately and efficiently processing and correlating data from multiple sensors due to parallax errors and differing data collection rates, leading to potential motion errors and delays in decision-making.
Innovation Solution
A configurable and dynamic sensor module system that utilizes a microcontroller to multiplex and correlate data from various sensors, including LiDAR, infrared, and thermal sensors, into a unified data packet, allowing for real-time processing and adaptive configuration based on environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If sensors are positioned at different locations to achieve comprehensive environmental coverage, then the field of view and detection capability are improved, but parallax errors occur due to data taken from different vantage points
Solution Approach 1:
The patent introduces a calibration engine as an intermediary component that processes and correlates data from multiple sensors positioned at different locations. The calibration engine applies calibration parameters to adjust and synchronize the data from each sensor, effectively mediating the parallax errors that arise from different vantage points while maintaining comprehensive environmental coverage
2Productivity
If multiple sensors operate at different data collection rates to optimize individual sensor performance, then each sensor can operate at its optimal response rate, but correlating the data becomes more complex and time-consuming
Solution Approach 1:
The patent implements a dynamic synchronization mechanism where the system adaptively adjusts the operation of multiple sensors based on real-time environmental conditions and navigation requirements. The calibration engine dynamically correlates data from sensors operating at different rates, adjusting correlation parameters in real-time to minimize data correlation time while maintaining each sensor's optimal response rate
Solution Approach 2:
The system employs feedback mechanisms where the calibration engine continuously monitors the performance and synchronization status of multiple sensors. Based on this feedback, the system adjusts calibration parameters and data correlation strategies to optimize both the response rate and the timing efficiency of data integration
3Measurement precision
If a large number of sensors are integrated to improve environmental representation accuracy, then the system can capture more comprehensive data, but the processing power and time required increase significantly
Solution Approach 1:
The patent divides the complex task of processing data from multiple sensors into segmented operations handled by specialized components. The calibration engine is segmented into specific functional modules that handle different aspects of data correlation (temporal alignment, spatial calibration, parameter synchronization), allowing parallel processing and reducing the overall processing power requirements while maintaining high environmental representation accuracy
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
Enables timely and accurate decision-making in autonomous navigation by ensuring efficient data correlation and processing, reducing errors and delays, and enhancing the system's responsiveness to its environment.
Implementation Method 1
A LIDAR system may be used to generate a three-dimensional (3D) map of an environment by emitting light and detecting reflected light from objects within the environment
Implementation Method 2
other sensor types within the sensor module may include infrared radiation (IR) sensors, thermal sensors, or other types of sensors
Implementation Method 3
other sensor types within the sensor module may include infrared radiation (IR) sensors, thermal sensors, or other types of sensors
Data Source
AI summary
The present disclosure relates generally to systems and methods for generating, processing and correlating data from multiple sensors in an autonomous navigation system, and more particularly to the utilization of configurable and dynamic sensor modules within light detection and ranging systems that enable an improved correlation between sensor data as well as configurability and responsiveness of the system to its surrounding environment.