Forklift Camera Point Cloud Scaling for Warehouse Space Measurement
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Solution Overview
Problem
Existing forklift truck assistance systems are expensive and prone to errors due to the hardware requirements of 3D cameras and methods like Structure from Motion (SfM) and Visual Simultaneous Localization and Mapping (vSLAM), necessitating a more cost-effective and robust solution for supporting operators in warehouse operations.
Innovation Solution
A method and system for a forklift truck that utilizes a camera to capture two-dimensional images, calculates a three-dimensional point cloud, applies a scaling factor to obtain absolute distances, and identifies free storage spaces or goods to be picked up using a scaled point cloud, leveraging existing on-board hardware and software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D cameras and vSLAM methods are used to reconstruct three-dimensional structures, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a digital copy (point cloud) of the three-dimensional environment using only two-dimensional camera images. Instead of using expensive 3D cameras to directly capture spatial data, the system processes 2D images through image processing algorithms to generate a scaled point cloud that accurately represents the warehouse environment's three-dimensional structure, thereby achieving 3D reconstruction without 3D sensing hardware
Solution Approach 2:
The patent replaces the mechanical/optical 3D sensing system (3D cameras, LiDAR) with a computational image processing system. By using 2D camera images combined with scaling factor calculation based on known reference object dimensions, the system substitutes complex hardware-based 3D measurement with software-based 3D reconstruction, reducing device complexity while maintaining measurement precision
2Measurement precision
If 3D cameras are used to capture environment data, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent uses inexpensive 2D camera images as the primary data source instead of expensive 3D imaging hardware. The system processes standard 2D images that can be captured by conventional cameras already present in many forklifts, eliminating the need for costly 3D cameras while achieving accurate three-dimensional measurements through computational scaling methods
Solution Approach 2:
The system creates an accurate digital replica of the physical environment using only 2D image data. By calculating scaling factors from known reference objects and applying them to the point cloud, the patent generates a cost-effective digital model that provides precise spatial information without requiring expensive 3D sensing equipment
3Device complexity
If unscaled point cloud is used to identify storage spaces, then device complexity is reduced, but manufacturing precision worsens
Solution Approach 1:
The patent transforms the unscaled point cloud data into a scaled representation by applying a scaling factor derived from known reference object dimensions. This parameter change converts relative spatial relationships into absolute measurements, enabling accurate determination of storage space dimensions and货物 sizes while maintaining the simplicity of using standard 2D camera images as the input data source
Data Source
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AI summary
Method for operating a forklift truck (50) in a warehouse, wherein the forklift truck (50) has a camera (54) and the method comprises the following steps: • Capturing a sequence of two-dimensional images with the camera (54), • Calculating a three-dimensional point cloud (64) based on the sequence of two-dimensional images, • Calculating a scaling factor for the point cloud (64) based on a first point of the point cloud and a second point of the point cloud (64), each representing a defined position in space, • Providing a scaled, three-dimensional point cloud (64) representing an environment of the forklift truck in the warehouse, • Identifying an area in the scaled, three-dimensional point cloud (64) representing a free storage space (66) or goods to be picked up (62), and • Calculating a dimension of the free storage space (66) or goods to be picked up (62).the goods to be received (62) based on the scaled, three-dimensional point cloud (64).