Mobile Vehicle Compute Offloading for Power and Weight Limits
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Solution Overview
Problem
The increasing demands for advanced functions, endurance, weight, and volume in aerial photography aircraft are hindered by the high power consumption of computing platforms, which is limited by battery energy density and the limitations of semiconductor technology, making it difficult to achieve miniaturization and extended flight while meeting intelligence and performance requirements.
Innovation Solution
A computation load distribution method and apparatus that determines whether to perform processing tasks locally on a mobile vehicle or remotely at a terminal based on task characteristics, using a data transmission link or telecommunication network to distribute the computation load, thereby reducing power consumption, weight, and size while enhancing intelligence and endurance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a powerful computing platform is used to support intelligent functions, then intelligence is improved, but power consumption increases
Solution Approach 1:
The patent segments the computing platform into two parts: a lightweight local processor on the aerial vehicle for basic real-time control, and a remote cloud computing server for intensive intelligent processing. This division allows the vehicle to maintain flight control capabilities while offloading power-consuming intelligent functions to the remote server, thereby improving intelligence without significantly increasing on-board power consumption.
2Extent of automation
If a powerful computing platform is used to support intelligent functions, then intelligence is improved, but weight increases
Solution Approach 1:
The patent extracts the heavy computing resources from the aerial vehicle and places them in a remote cloud server. The vehicle retains only essential lightweight components for flight control and basic sensing, while intelligent processing functions are taken out and executed remotely. This extraction dramatically reduces the weight of the computing platform on the vehicle while maintaining intelligent capabilities through network connectivity.
3Extent of automation
If a powerful computing platform is used to support intelligent functions, then intelligence is improved, but flight duration decreases
Solution Approach 1:
By extracting power-consuming computing functions from the aerial vehicle to a remote server, the patent reduces the energy load on the vehicle's battery system. This extraction enables extended flight duration as the battery no longer needs to power intensive processing operations, while intelligent functions continue to operate through the vehicle's communication link to the remote computing platform.
4Use of energy by moving object
If semiconductor process advances are used to reduce power consumption, then power consumption is reduced, but manufacturing complexity increases
Solution Approach 1:
The patent introduces a communication network as an intermediary between the aerial vehicle and the computing platform. Instead of relying on complex semiconductor advances to reduce power consumption on the vehicle, the system uses the communication network to transfer data to a remote server for processing. This intermediary approach reduces power consumption without requiring the vehicle to incorporate complex advanced semiconductor manufacturing, thereby avoiding increased manufacturing complexity.
Data Source
AI summary
A computation load distribution method includes determining a processing task associated with a mobile vehicle, and determining one or more processing resources for performing the processing task based at least partially on characteristics of the processing task. Determining the one or more processing resources includes determining whether to perform the processing task locally at the mobile vehicle and/or remotely at a remote terminal.