Centralized Camera Control for AGV Traffic Collision Avoidance
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Solution Overview
Problem
Automated guided vehicles (AGVs) face inefficiencies in collision avoidance due to camera blockages by cargo and the need for multiple scheduling devices to process extensive visual data, leading to reduced control efficiency and increased resource consumption.
Innovation Solution
Implementing a method where cameras in the workplace collect visual data from traffic management areas, allowing the scheduling device to control AGVs based on unified visual data, using indicator lights and voice prompts to manage traffic and prevent collisions, and enabling AGVs to adjust paths or speeds to avoid obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a camera is installed on the AGV to collect visual data for obstacle detection, then the AGV can determine obstacle positions and control movement to avoid collisions, but the camera may be blocked by transported cargos, making obstacle detection impossible and reducing control efficiency
Solution Approach 1:
The system divides the detection function into two parts: a fixed camera on the workplace that captures visual data of the entire area, and multiple AGVs that receive processed detection results. This segmentation eliminates the need for each AGV to have its own camera, solving the blockage problem while maintaining detection reliability.
Solution Approach 2:
The scheduling device acts as an intermediary that receives visual data from the fixed camera, processes it to identify obstacles and moving objects, then transmits this information to relevant AGVs. This intermediary approach allows centralized detection without requiring cameras on each moving vehicle.
2Speed
If each AGV collects and processes visual data independently for collision avoidance, then each AGV can make real-time decisions, but multiple scheduling devices process extensive visual data leading to increased resource consumption and reduced control efficiency
Solution Approach 1:
The system merges the detection and processing functions into a single centralized scheduling device that handles visual data from the fixed camera. Individual AGVs only receive processed results and execute pre-determined avoidance actions, eliminating redundant processing across multiple devices and reducing overall computational resource consumption.
Solution Approach 2:
The scheduling device performs preliminary analysis of visual data to identify obstacles and determine which AGVs need to take avoidance actions. By pre-processing the data and determining control strategies before transmitting to AGVs, the system enables rapid AGV response without requiring each AGV to perform extensive real-time analysis.
Data Source
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AI summary
Provided are a method and apparatus for controlling an automated guided vehicle, and a storage medium, which fall within the technical field of electronics. The method comprises: acquiring visual data in a visual region of a target camera mounted in a working place, the visual region being a range where the target camera carries out visual data collection in a traffic management region on an AGV travel path; detecting a moving object in the visual region of the target camera based on the visual data; and controlling an AGV currently in an operating state when it is determined through detection that there is a moving object present in the visual region. According to the method, an AGV currently in an operating state is controlled when it is determined through detection that there is a moving object present in the visual region of the target camera. The target camera can carry out visual data collection in a traffic management region on an AGV travel path, thereby ensuring the management of an AGV needing traffic management, so that the occurrence of a collision accident of an AGV is reduced.