Visual Object Localization Using Reprojection Error for Autonomous Driving
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately localizing objects, such as stop signs, due to varying estimates from different localization techniques, leading to potential incorrect reactions and navigation issues.
Innovation Solution
A method and system that utilize multiple localization techniques (object size, depth map, and roadgraph-based) to identify and verify the location of objects by calculating error scores based on reprojection errors, selecting the most accurate estimate for controlling the vehicle's autonomous driving mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple localization techniques are used to determine object locations, then the reliability of object localization is improved, but the device complexity increases
Solution Approach 1:
The patent combines multiple localization techniques (object size-based localization, depth map-based localization, and roadgraph-based localization) into a unified system that processes results from all techniques simultaneously. The processor integrates estimates from each technique and uses reprojection error calculation to evaluate and select the most accurate estimate, thereby improving reliability through combination while managing complexity through systematic integration.
2Measurement precision
If multiple localization techniques are used to determine object locations, then the measurement precision is improved, but the computational resources required increase
Solution Approach 1:
The patent changes the evaluation parameter from simply counting the number of localization techniques to calculating reprojection errors for each estimated location. By introducing this error metric, the system can identify the most accurate estimate without necessarily using all available techniques with equal weight, thereby improving measurement precision while optimizing computational energy consumption through selective processing.
3Measurement precision
If reprojection errors are calculated to verify estimated locations, then the measurement precision is improved, but the loss of time increases
Solution Approach 1:
The patent performs preliminary actions by calculating reprojection errors for each estimated location before final selection. By pre-evaluating all estimates using the reprojection error metric, the system ensures that the most accurate location is selected without requiring additional time-consuming verification steps later, thus improving measurement precision while managing processing time through advance evaluation.
Data Source
AI summary
Aspects of the disclosure relate to verifying the location of an object of a particular type. For instance, a plurality of images of an environment of the vehicle may be received. Associated objects of the particular type may be identified in ones of the plurality of images. A plurality of estimated locations may be determined for the object using a plurality of different localization techniques. For each image of the ones of the plurality of images, determine a reprojection error for each of the plurality of estimated locations. For each of the plurality of estimated locations, an error score is determined based on the reprojection errors. An estimated location may be selected from the plurality of estimated locations based on the determined error score. This selected location may be used to control a vehicle in an autonomous driving mode.