AGV Channel Monitoring Using Lidar and Cameras for Worker Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In yarn spindle production workshops, the use of automated guided vehicles (AGVs) poses a risk of collisions with workers due to shared pathways, leading to potential accidents and injuries, necessitating an effective monitoring solution.
Innovation Solution
A channel monitoring method utilizing lidar and cameras to detect target objects in real-time, generating precise warning information to avoid collisions by adjusting AGV operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AGV moves along a predetermined path in a shared pathway, then transportation efficiency is improved, but collision risk with workers increases
Solution Approach 1:
The system performs preliminary detection of workers in the AGV's path using image recognition before the collision can occur. The warning information is generated in advance, allowing the AGV to take preventive action (stop or alter path) before the harmful collision event happens.
Solution Approach 2:
The system continuously monitors the environment around the AGV using image collection devices, processes the images to detect workers, and provides real-time feedback through warning information. This closed-loop feedback enables dynamic adjustment of AGV operation to avoid collisions while maintaining efficient transportation.
2Reliability
If multiple channels are monitored simultaneously, then safety coverage is improved, but processing time increases
Solution Approach 1:
The monitoring system divides the workspace into multiple independent channels, each with its own detection and warning mechanisms. This segmentation allows parallel processing of multiple channels simultaneously, maintaining comprehensive safety coverage without sequentially increasing total processing time.
Solution Approach 2:
Each channel's image collection device and processing system operates independently and autonomously, performing its own detection and generating its own warning information. This self-service capability of each channel enables simultaneous monitoring of multiple channels without requiring centralized sequential processing, thus maintaining fast response times across all channels.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Improves processing efficiency and accuracy of target object detection, enhancing response efficiency and safety in yarn spindle production workshops by reducing accidents and ensuring normal operations.
Implementation Method 1
obtaining scan data collected by a vehicle body collection component of the AGV in an area around a vehicle body
Implementation Method 2
obtaining video data collected by a camera in a video collection area
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
The present disclosure provides a channel monitoring method and apparatus, an electronic device, and a storage medium. The method includes: obtaining scan data collected by a vehicle body collection component of an automated guided vehicle, AGV, in an area around a vehicle body (S101); obtaining video data collected by a camera in a video collection area (S102); in a case of determining an existence of a target object based on the scan data collected by the vehicle body collection component and/or the video data collected by the camera, obtaining a target channel where the target object is located (S103); and generating target warning information for the target channel where the target object is located (S104).