AGV 3D Datacenter Mapping With Camera-LiDAR Correlation

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Solution Overview

Problem

Existing datacenter inventory management systems face challenges in accurately tracking and updating the contents of datacenter racks due to reliance on manual entry and potential inaccuracies, lacking efficient automated solutions for correcting errors.

Innovation Solution

An automated imaging system utilizing an automated guided vehicle (AGV) equipped with cameras and a laser imaging system to capture and correlate images with distance data, generating accurate, real-time maps and inventory information of datacenter contents without human intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual entry methods are used to store datacenter rack content information, then the system is simple to operate, but the accuracy of rack content information deteriorates

Engineering Contradiction:
Improverack content information accuracyVSAvoidimaging system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The system enables self-service by allowing the datacenter environment to be automatically imaged and documented without human intervention. The AGV autonomously navigates, captures images, and the system automatically processes this data to update inventory records, eliminating the need for manual entry while maintaining simplicity of operation.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

Manual mechanical entry methods are replaced with an automated optical imaging system. The system uses cameras to capture images, processes them through image recognition algorithms, and automatically updates inventory databases, substituting human manual operations with automated mechanical and computational systems.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If conventional imaging systems with overlapping fields of view are used, then complete coverage is achieved, but the complexity of processing and correlating images increases

Engineering Contradiction:
Improvedatacenter mapping accuracyVSAvoidimage processing complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The datacenter environment is divided into multiple discrete zones, each captured by a dedicated camera with a non-overlapping field of view. This segmentation approach simplifies processing by assigning each image to a specific spatial region, eliminating the need for complex overlapping image correlation while ensuring complete coverage through systematic zone-by-zone mapping.

Inventive Principle:
Principle #1Segmentation

3Productivity

If automated guided vehicles with multiple cameras and laser systems are deployed, then imaging precision and coverage improve, but the cost and complexity of the system increase

Engineering Contradiction:
Improvedatacenter monitoring efficiencyVSAvoidvehicle system complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The AGV is designed as a universal platform that performs multiple functions: navigation via laser imaging, datacenter mapping, rack content imaging, and autonomous return to base. By consolidating these diverse functions into a single multi-functional vehicle, the system achieves high productivity without proportionally increasing complexity, as the same hardware platform executes multiple tasks.

Inventive Principle:
Principle #6Universality (Multi-functionality)

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

The system provides precise, automated tracking and updating of datacenter contents, enhancing accuracy and efficiency in inventory management by generating detailed maps and location data, reducing manual errors and improving datacenter monitoring.

Implementation Method 1

a laser imaging system, the laser imaging system configured to scan a physical area to obtain respective distances between the vehicle and a plurality of locations within the physical area

Methodology Applied
Scientific EffectLIDAR: LIDAR

Implementation Method 2

an optical imaging system, the optical imaging system including a plurality of cameras, the cameras each being configured to have a respective field of view

Methodology Applied
Scientific EffectLight detection: Light

Data Source

PatentEP4012531B1Autonomous system for 3D mapping of a datacenter
Publication Date: 2023.08.30 GOOGLE LLC
  • EP4012531B1 patent drawingFigure 1A
  • EP4012531B1 patent drawingFigure 1B
  • EP4012531B1 patent drawingFigure 1C~1D

AI summary

An automated datacenter imaging system is provided, including an automated guided vehicle having a housing. The system includes an optical imaging system coupled to the housing comprising a plurality of cameras each configured to have a respective field of view, the fields of view being at least partially non-overlapping with one another. The system may include a laser imaging system coupled to the housing and configured to scan the datacenter to obtain a plurality of distances between the housing and a plurality of locations within the datacenter. The system may include an image processor configured to correlate a plurality of images taken by the cameras with the plurality of distances taken by the laser imaging system into a single mosaic map, the image processor being configured to locate the plurality of images and the plurality of distances relative to a known coordinate system of the datacenter.