Forklift Camera Positioning With Scaled 3D Point Clouds
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Solution Overview
Problem
Existing forklift truck assistance systems are expensive and prone to errors due to the hardware requirements, and there is a need for improved operational safety and support for operators.
Innovation Solution
A method using a camera mounted at a fixed height on the forklift truck to capture two-dimensional images, calculate a three-dimensional point cloud, apply a scaling factor, and continuously determine the truck's position for navigation and collision avoidance, utilizing existing camera hardware and software.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D cameras, LiDAR scanners, or distance sensors are used for environmental scanning, then measurement precision and reliability are improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses a 2D camera to capture images that are then processed to create a scaled 3D point cloud representation of the environment. Instead of directly using expensive 3D sensors, the system creates a computational copy of the 3D environment from 2D images through SfM and vSLAM algorithms, achieving similar functional results with simpler hardware
Solution Approach 2:
The patent replaces mechanical/optical 3D sensing systems (3D cameras, LiDAR, distance sensors) with a computational approach using 2D image processing. The mechanical system of active 3D sensing is substituted by optical capture followed by algorithmic reconstruction, reducing hardware complexity while maintaining measurement capability
2Reliability
If multiple sensors and tracking systems are deployed, then navigation reliability is improved, but cost and device complexity increase
Solution Approach 1:
The patent makes the 2D camera perform multiple functions: it captures images for both visual navigation assistance and for generating 3D point clouds through SfM/vSLAM. The same hardware component serves dual purposes, reducing the need for separate specialized sensors while maintaining navigation reliability
Solution Approach 2:
The system uses the forklift's existing camera infrastructure to serve the additional function of 3D environmental mapping and position tracking. Rather than adding external tracking hardware, the system makes the existing camera system work harder by processing its output through computational algorithms to derive position and 3D structure information
3Reliability
If advanced 3D sensing hardware is used, then collision avoidance capability is improved, but cost increases
Solution Approach 1:
The patent creates a scaled 3D point cloud copy of the warehouse environment using 2D camera images processed through SfM and vSLAM. This computational model serves as a virtual representation for collision detection, replacing the need for expensive dedicated 3D sensing hardware while maintaining the ability to detect obstacles and prevent collisions
Data Source
Figure 1~2
AI summary
Method for operating a forklift (10) in a warehouse, wherein the forklift has a camera (14) arranged at a fixed height on the forklift, and the method comprises the following steps: · Capturing a sequence of two-dimensional images with the camera (14), · Calculating a three-dimensional point cloud based on the sequence of two-dimensional images, · Calculating a scaling factor for the point cloud based on a first point of the point cloud and a second point of the point cloud, each representing a defined position in space, · Providing a scaled, three-dimensional point cloud (22) representing an environment of the forklift (10) in the warehouse, and · Continuously calculating a current position of the forklift (10) in space based on a current position of the camera (14), which is determined using current two-dimensional images and the scaled,three-dimensional point cloud (22) is determined, · Evaluation of the current position of the industrial truck (10) for navigation in the warehouse and/or for collision avoidance.,