Cloud-Edge-End UAV Control for 5G Rescue Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current UAVs for security rescue have limited control distance and high latency in data transmission, which restricts their flight range and accuracy in complex terrain detection and rescue missions due to reliance on 2.4 G/5.8 G wireless frequencies and 4G mobile technology, leading to high energy consumption and inadequate precision in GPS positioning.
Innovation Solution
A cloud-edge-end cooperative control method using a 5G networked UAV with a single-chip microcomputer, detection sensors, and a control platform for bidirectional communication between the UAV, edge cloud, and core cloud, enabling sparse landmark map building, three-dimensional dense map creation, and high-precision semantic map generation, with image acquisition and video processing distributed across these layers to reduce latency and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If all computations are carried out on a cloud side through traditional optical fiber infrastructure, then computing power is sufficient for complex tasks, but latency increases to tens or hundreds of milliseconds and data transmission cost increases
Solution Approach 1:
The patent segments the computing system into three layers: edge cloud (for real-time SLAM and navigation computations), core cloud (for non-real-time video analysis and data processing), and UAV onboard (for basic control). This segmentation allows critical real-time computations to be performed locally at the edge cloud with low latency, while non-critical tasks use traditional cloud infrastructure.
Solution Approach 2:
The patent introduces an edge cloud as an intermediary between the UAV and the core cloud. The edge cloud processes real-time navigation and SLAM computations locally, acting as a mediator that reduces the need for high-latency communication with the core cloud for time-sensitive operations.
2Speed
If video analysis and data computation are carried out on a UAV side, then real-time processing is achieved, but the UAV needs to be equipped with an expensive high-performance computing platform and power consumption increases
Solution Approach 1:
The patent extracts the high-performance computing tasks (SLAM, dense map building, semantic segmentation) from the UAV and relocates them to the edge cloud. The UAV retains only basic onboard processing for immediate control, significantly reducing its power consumption while maintaining real-time processing capabilities through edge cloud connectivity.
3Ease of operation
If 2.4G/5.8G wireless frequency bands or 4G are used for communication, then the UAV can be controlled manually, but control distance is limited and flight range is restricted
Solution Approach 1:
The patent merges multiple communication technologies: 5G for high-speed data transmission between UAV and edge cloud, and traditional 2.4G/5.8G for manual control. This combination allows the UAV to extend its flight range using 5G for autonomous operations while retaining manual control capability over longer distances through the traditional wireless bands.
Data Source
AI summary
The present invention discloses a cloud-edge-end cooperative control method of a 5G networked UAV for security rescue, including: an image acquisition step: performing, by a single-chip microcomputer, attitude resolution on data acquired by a detection sensor, to obtain image data; a sparse landmark map building step: performing, by a control platform, front-end feature point matching, local map building and optimization, loopback detection, and frame resolution on the image data, to generate a sparse landmark map; a three-dimensional dense map building step: generating, by an edge cloud, a three-dimensional dense map based on a key frame pose and key frame observation data of the sparse landmark map; a high-precision semantic map building step: obtaining a high-precision semantic map; and a UAV movement step: adjusting, by the driving mechanism, a pose of the UAV according to the three-dimensional dense map or the high-precision semantic map.