Vehicle Wheel Slip Detection Using Visual Odometry
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating due to the vast amounts of data from various sources, such as cameras, GPS, and sensors, which can lead to storage and processing issues, and traditional mapping technologies require significant data updates, posing difficulties in efficient navigation.
Innovation Solution
The system employs cameras to analyze images and process data to determine vehicle motion, predict wheel rotation, detect wheel slip conditions, and initiate navigational actions, using a processor with memory to execute instructions for autonomous navigation, and includes a server-based system to correlate wheel slip indicators with geographic locations for generating navigational information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional mapping technology and multiple sensors are used for autonomous navigation, then navigation accuracy is improved, but data storage requirements and processing complexity increase significantly
Solution Approach 1:
The patent extracts and removes unnecessary data from the navigation system by using visual odometry to calculate vehicle position and orientation directly from camera images, eliminating the need to store and process large volumes of GPS, accelerometer, and suspension sensor data that were traditionally required for accurate navigation
Solution Approach 2:
The patent segments the navigation problem into independent visual feature detection and tracking components, processing only relevant visual information from camera images rather than integrating and processing data from multiple sensor sources, thereby reducing overall data storage requirements
2Measurement precision
If traditional mapping technology and multiple sensors are used for autonomous navigation, then navigation accuracy is improved, but processing complexity increases significantly
Solution Approach 1:
The patent extracts and removes complex data processing requirements by implementing visual odometry that calculates vehicle motion directly from sequential camera images, eliminating the need to process and integrate data from GPS, accelerometers, suspension sensors, and other multiple sensor sources
Solution Approach 2:
The patent replaces complex mechanical sensor systems and their associated processing requirements with a visual-based odometry system that uses image processing algorithms to determine vehicle position and orientation, thereby reducing processing complexity
3Quantity of substance
If visual information from cameras is used for navigation, then data storage needs are reduced, but the ability to detect wheel slip conditions deteriorates
Solution Approach 1:
The patent merges visual odometry data with wheel rotation sensor data in a unified wheel slip detection algorithm, combining the advantages of both visual information (reduced data storage) and sensor information (accurate wheel slip detection) to achieve reliable wheel slip detection with minimal data storage requirements
Solution Approach 2:
The patent introduces visual odometry as an intermediary that bridges camera images and wheel rotation sensors, using visual feature tracking to provide contextual information that enhances wheel slip detection accuracy while maintaining low data storage requirements
4Reliability
If real-time wheel slip detection is implemented, then navigation safety is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary calculations of expected wheel rotation based on visual odometry data before comparing it with actual sensor readings, pre-processing visual feature tracking information to enable rapid wheel slip detection without requiring extensive real-time computation
Solution Approach 2:
The patent implements partial wheel slip detection by monitoring only critical wheels or using simplified detection thresholds, performing sufficient detection to ensure navigation safety without the computational overhead of analyzing all wheels in detail
Data Source
AI summary
The present disclosure relates to systems and methods for identifying a wheel slip condition. In one implementation, a processor may receive a plurality of image frames acquired by an image capture device of a vehicle. The processor may also determine based on analysis of the images one or more indicators of a motion of the vehicle; and determine a predicted wheel rotation corresponding to the motion of the vehicle. The processor may further receive sensor outputs indicative of measured wheel rotation associated with a wheel; and compare the predicted wheel rotation to the measured wheel rotation for the wheel. The processor may additionally detect a wheel slip condition wheel based on a discrepancy between the predicted wheel rotation and the measured wheel rotation; and initiate at least one navigational action in response to the detected wheel slip condition associated with the wheel.