Autonomous Sensor Fusion Configuration for Parallax-Aware Navigation
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Solution Overview
Problem
Existing autonomous navigation systems face challenges in efficiently processing and correlating data from multiple sensors due to varying operational requirements and parallax errors, leading to potential motion errors and delays in decision-making.
Innovation Solution
A dynamic sensor system with configurable modules that integrate various sensors, including LiDAR, thermal, and IR, using a microcontroller to multiplex and demultiplex data, apply calibration parameters, and generate unified data packets for timely and accurate navigation decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple discrete sensors are integrated into autonomous navigation systems, then the system can gather more environmental data, but the processing time and computational complexity increase significantly
Solution Approach 1:
The patent segments sensor data processing by creating separate processing pipelines for different sensor types (LIDAR, cameras, radar, etc.) and different data stages (acquisition, preprocessing, correlation, interpretation). This modular segmentation allows parallel processing of multiple sensor streams simultaneously, reducing overall processing time while maintaining complete environmental data capture
Solution Approach 2:
The patent implements preliminary action by performing sensor data preprocessing and correlation operations before full autonomous navigation decisions are required. Configuration parameters are pre-calculated based on vehicle motion state, and sensor data is pre-correlated in a buffer, so that when navigation decisions are needed, the processed data is already ready for rapid interpretation
2Area of stationary object
If sensors are positioned at different locations on the vehicle, then the field of view is improved, but parallax errors and motion errors increase
Solution Approach 1:
The patent introduces an intermediary correlation process that mediates between sensors at different vehicle locations. A correlation engine uses configuration parameters (sensor positions, orientations, vehicle motion state) to mathematically transform and align sensor data into a common reference frame, eliminating parallax errors while preserving the expanded field of view provided by distributed sensor placement
Solution Approach 2:
The patent dynamically changes configuration parameters based on vehicle motion state (acceleration, steering angle, speed). By adjusting correlation parameters in real-time according to actual vehicle dynamics, the system compensates for motion-induced errors and maintains measurement precision across all sensors regardless of their positions on the vehicle
3Measurement precision
If sensor data correlation and processing are performed before navigation decisions, then decision accuracy is improved, but the response time for timely actions is delayed
Solution Approach 1:
The patent performs preliminary correlation and preprocessing of sensor data continuously in the background, maintaining a ready buffer of processed information. When navigation decisions are required, the system only needs to interpret already-correlated data rather than performing full correlation from scratch, thus maintaining high decision accuracy while enabling rapid response
Solution Approach 2:
The patent implements dynamic processing where the depth and extent of data correlation adapt based on situational context. In normal conditions, full correlation is performed for accuracy. In urgent situations requiring rapid response, the system dynamically reduces processing depth for already-correlated data, prioritizing speed while maintaining sufficient accuracy through the pre-established correlation foundation
Data Source
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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.