Depth-Sensing Camera Pallet Dimensioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for calculating the dimensions of objects on pallets for shipping are either expensive, complex, or lack accuracy, particularly for box freight and skidded freight, as they require elaborate framing and trained technicians, and cannot distinguish between objects or account for non-cubic shapes.
Innovation Solution
A system utilizing depth-sensing imaging devices to generate depth maps, transform them into a 3D world coordinate system, and calculate the volume of objects by determining edge lengths and height, allowing for accurate dimensioning of pallets with or without forklifts, using cameras like RGB-D or infrared-based sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser-based dimensioners are used, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex mechanical laser-based dimensioning systems with a simplified camera-based optical system. Instead of using expensive laser scanners with moving parts and elaborate framing, the invention uses standard depth-sensing cameras (such as RGB-D cameras) to capture images and calculate dimensions through image processing algorithms, thereby reducing device complexity while maintaining measurement capability
Solution Approach 2:
The patent creates a digital copy of the physical object through image capture and processing. By capturing images of the object and generating a point cloud representation, the system derives dimensional information from this digital replica without requiring direct physical measurement devices, simplifying the overall system architecture
2Ease of manufacture
If ultrasonic sensors are used, then cost is reduced, but measurement precision and productivity worsen
Solution Approach 1:
The patent replaces contact-based ultrasonic sensing with non-contact optical sensing using depth cameras. This substitution eliminates the need for manual object placement and physical contact, allowing automatic dimensioning of objects in various positions and orientations, thereby improving both measurement precision and productivity while keeping costs low
Solution Approach 2:
The patent transitions from 2D ultrasonic range data to 3D spatial information captured by depth cameras. The depth maps and point clouds provide rich three-dimensional data that enables accurate calculation of length, width, height, and volume without requiring manual intervention or specific object positioning
3Device complexity
If conventional manual methods are used, then device complexity is reduced, but productivity and measurement precision worsen
Solution Approach 1:
The patent implements an automated system that performs dimensioning independently without human intervention. The camera captures images, the processor automatically generates point clouds, and the system calculates dimensions and volume autonomously, eliminating manual measurement steps while maintaining system simplicity
Solution Approach 2:
The patent replaces manual mechanical measurement tools with automated optical sensing and computational processing. The system uses image capture and algorithmic processing to automatically determine dimensions, significantly increasing productivity compared to manual methods while keeping the physical infrastructure simple
4Measurement precision
If existing dimensioning systems are used, then measurement capability is improved, but adaptability worsens due to inability to distinguish objects or account for non-cubic shapes
Solution Approach 1:
The patent uses 3D point cloud data from depth cameras to represent objects in three-dimensional space, enabling the system to capture and analyze complex geometries. This 3D representation allows accurate volume calculation for non-cubic shapes and distinguishes different object forms, greatly improving adaptability while maintaining measurement precision
Solution Approach 2:
The patent calculates multiple dimensional parameters (length, width, height, volume) from the point cloud data and uses these parameters to characterize different objects. By computing various geometric parameters rather than relying on a single measurement, the system can distinguish between different object types and adapt to diverse shipping scenarios
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
Provides a cost-effective and accurate method for determining shipping volumes, capable of handling complex shapes and integrating with existing systems for billing, with improved productivity and reduced wear and tear on mechanical parts.
Implementation Method 1
using cameras like RGB-D or infrared-based sensors
Implementation Method 2
generate depth maps of an object placed on a dimensioning surface
Data Source
AI summary
The present disclosure relates to calculating dimensions of loaded or partially loaded pallets for purposes of billing. A plurality of cameras are utilized to determine dimensions of a package placed in bounding volume for shipping.