Sensor Timestamp Synchronization for Enhanced Image Fusion
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Solution Overview
Problem
Autonomous vehicles face challenges in generating enhanced images of their environment for accurate object detection and route planning, as existing systems struggle to synchronize and align data from different sensors, leading to inefficiencies in multi-modal sensor fusion and calibration.
Innovation Solution
A system that includes a first sensor for scanning an area of interest and a second sensor for capturing images, with a controller that synchronizes and compares timestamp information to select a base image, merging multiple images into an enhanced image frame for improved object detection and trajectory planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are used to scan and capture images of the environment, then object detection accuracy and route planning reliability are improved, but data synchronization and alignment complexity increase
Solution Approach 1:
The patent introduces timestamp information as an intermediary element that mediates between multiple sensors and the processing system. Each sensor data packet is tagged with a timestamp, allowing the system to synchronize and align data from different sensors (lidar, cameras, etc.) based on these temporal markers without requiring complex direct coordination between sensors. This resolves the contradiction by maintaining high reliability through multi-sensor fusion while reducing synchronization complexity through the use of timestamps as a mediating mechanism.
2Measurement precision
If multiple images are merged into an enhanced image frame, then image quality and object detection capability are improved, but processing time and computational requirements increase
Solution Approach 1:
The patent applies preliminary action by selecting a base image from the multiple captured images before performing the merging operation. This base image selection is done based on criteria such as image quality, timestamp recency, or detection confidence. By pre-selecting the base image, the system reduces the computational burden of merging, as subsequent sensor data and images are aligned to this predetermined reference rather than requiring complex pairwise comparisons of all images. This maintains high measurement precision through careful base selection while reducing processing time through the preliminary action of base image choice.
3Measurement precision
If timestamp comparison is used to select a base image, then data alignment accuracy is improved, but processing overhead increases
Solution Approach 1:
The patent replaces complex mechanical or algorithmic image alignment mechanisms with a simpler timestamp-based selection system. Instead of using computationally intensive feature matching or geometric transformation methods to align images and sensor data, the system uses timestamp comparison to identify the base image and align subsequent data to it. This substitution of a simple temporal comparison mechanism for complex alignment algorithms maintains high data alignment accuracy while significantly reducing processing overhead and energy consumption.
Data Source
AI summary
Described examples relate to an apparatus comprising a first sensor configured to scan an area of interest during a first time period and a second sensor configured to capture a plurality of images of a field of view. The apparatus may include at least one controller configured to receive the plurality of images captured by the second sensor, compare the timestamp information associated with at least one image of the plurality of images to at least one time period of the first time period, and select a base image from the plurality of images based on the comparison.