Vehicle Navigation Using Delta Imaging for Low-Power Obstacle Detection
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Solution Overview
Problem
Conventional control systems for autonomous and semi-autonomous vehicles face challenges in achieving near-perfect safety due to the complexity of handling unforeseen obstacles and high-speed interactions, which requires extensive sensor arrays and significant processing power, leading to limitations in cost, energy efficiency, and real-time responsiveness.
Innovation Solution
The implementation of delta imaging techniques, which process delta images to identify objects and determine their characteristics, such as speed and acceleration, using artificial neural networks, allowing for reduced sensor reliance and processing power consumption by focusing on delta information within images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If numerous sensors and sensor types are used to ensure safety and detect all obstacles, then safety and detection capability are improved, but cost and device complexity increase
Solution Approach 1:
The patent merges multiple sensor functions into a single camera system. The camera captures images that are processed to extract multiple types of information (object detection, depth estimation, motion detection) that would traditionally require separate sensors. This consolidation reduces device complexity while maintaining comprehensive environmental awareness for safety
Solution Approach 2:
The camera system is designed to perform multiple functions simultaneously: detecting stationary objects, tracking moving objects, estimating depth, and determining object characteristics. This multi-functional approach replaces what would traditionally require multiple specialized sensors, reducing overall system complexity while improving reliability
2Reliability
If numerous sensors are equipped to autonomous vehicles, then safety and detection capability are improved, but energy consumption increases
Solution Approach 1:
The patent consolidates multiple energy-consuming sensor operations into a single camera system. By processing images to extract multiple types of information simultaneously, the system reduces the total energy consumption compared to running multiple separate sensors, while maintaining comprehensive safety monitoring
Solution Approach 2:
The system uses frame-by-frame image processing to detect changes and moving objects. By comparing successive frames and processing only the delta information (changes between frames), the system reduces computational load and energy consumption while maintaining continuous monitoring capability for safety
3Productivity
If massive computer processing power is used to interpret sensor data in real-time, then response speed and accuracy are improved, but energy consumption and system complexity increase
Solution Approach 1:
The patent extracts only the essential and changing information from continuous image streams by processing delta images (differences between frames). This extraction approach focuses computational power on detecting and analyzing only the relevant changes in the environment, improving response speed while reducing overall processing requirements and energy consumption
Solution Approach 2:
The image processing is segmented into distinct stages: capturing full frames, computing delta images to identify changes, detecting objects in delta regions, and tracking their characteristics. This segmentation allows the system to allocate processing power efficiently, focusing intensive analysis only where needed rather than processing all image data uniformly
Data Source
AI summary
A system and method for forecasting perceived transitions to the four annual seasons in geographic areas is disclosed. The perceived transitions are identified by comparing forecasted daily temperatures in each geographic area to thresholds generated based on normal daily temperatures in those geographic areas. The forecasted daily temperatures may be calculated using both forecasted temperatures and forecasted perceived ambient temperatures (calculated using both temperature and humidity, cloud cover, sun intensity, and/or wind speed).