Multi-Camera Positioning via Coordinate Transformation for Warehouse Dispatch
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Solution Overview
Problem
Current methods lack effective positioning and dispatching of workers and automated guided vehicles in warehouses, leading to inefficient warehouse management and increased delivery times due to insufficient space or improper storage, resulting in wasted manpower.
Innovation Solution
A multi-camera positioning and dispatching system that uses a network of cameras and processing devices to create a panoramic map of indoor spaces, converting pixel coordinates to world coordinates, and projecting working units onto this map for precise positioning and task assignment, optimizing the movement paths of vehicles and personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple cameras are deployed to cover large warehouse areas, then positioning accuracy is improved, but system complexity increases
Solution Approach 1:
The warehouse space is divided into multiple overlapping coverage areas, each monitored by a separate camera. The system segments the large monitoring task into smaller regional tasks, with each camera responsible for a specific area. This allows accurate positioning within each local area while keeping individual camera systems simple and manageable.
Solution Approach 2:
The patent introduces coordinate transformation as an intermediary process that bridges the gap between multiple camera coordinate systems and a unified warehouse coordinate system. By converting coordinates from different camera perspectives through intermediate transformation steps, the system achieves integrated positioning without requiring direct complex inter-camera coordination.
2Measurement precision
If coordinate transformation is performed for each camera view, then positioning precision is improved, but processing time increases
Solution Approach 1:
The system pre-establishes transformation relationships between all camera coordinate systems and the warehouse coordinate system before actual positioning operations. By preparing transformation matrices and parameters in advance, the system avoids performing complex calculations in real-time, thus maintaining high positioning precision while reducing processing delays during actual use.
3Productivity
If automated guided vehicles are used to perform repetitive works, then productivity is improved, but dispatching efficiency deteriorates due to lack of positioning methods
Solution Approach 1:
The system implements real-time feedback by continuously tracking the positions of automated guided vehicles and working units through the camera network. This position information is fed back to the dispatching system, enabling dynamic adjustment of task assignments and route planning. The feedback mechanism transforms the previously intractable dispatching problem into a manageable optimization task based on current state information.
Data Source
AI summary
A multi-camera positioning and dispatching system includes a plurality of cameras and processing device. The cameras are disturbed over an indoor space having a plurality of areas; the cameras are corresponding to the areas and capture the images of the areas respectively. The processing device converts the pixel coordinates of the image of the camera corresponding to each area into the camera coordinates of the area, and converts the cameras coordinates of the area into the world coordinates of the area so as to integrate the images with one another and obtain a panoramic map, defined by a world coordinate system, of the indoor space. The processing device projects the working unit in the image captured by any one of the cameras to the panoramic map. The system can achieve positioning function via the panoramic map so as to optimize indoor environment management and save manpower.