Warehouse UAV 3D Mapping for GPS-Free Indoor Navigation
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Solution Overview
Problem
Existing drone systems for warehouse management face limitations in indoor navigation due to reliance on GPS, 2D flight planning, and lack of effective 3D object space mapping, leading to inefficiencies and increased risk of errors.
Innovation Solution
A UAV system equipped with cameras, sensors, and a programmable processor that generates a 3D object-space map, estimates its position and orientation, and autonomously navigates while performing static and dynamic obstacle avoidance, and finding the optimal path within the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS-dependent navigation is used, then outdoor navigation capability is achieved, but indoor navigation reliability deteriorates due to inadequate GPS signal access
Solution Approach 1:
The patent introduces visual odometry and SLAM algorithms as intermediary systems that enable the UAV to navigate indoors without GPS. The system uses onboard cameras and sensors to create visual landmarks and map the environment, serving as a mediator between the UAV and the indoor space where GPS is unavailable. This allows the UAV to maintain navigation reliability across both indoor and outdoor environments.
Solution Approach 2:
The patent replaces the GPS-based mechanical navigation system with a vision-based navigation system using visual odometry and SLAM. Instead of relying on satellite signals, the system substitutes a camera-based approach that processes visual information to determine position and orientation, enabling reliable indoor navigation where GPS fails.
2Ease of operation
If 2D flight planning is used, then simple path control is achieved, but 3D object avoidance capability deteriorates
Solution Approach 1:
The patent transitions from 2D flight planning to 3D navigation by incorporating vertical dimension awareness through visual odometry and SLAM. The system generates three-dimensional maps and calculates positions in 3D space, enabling the UAV to perform obstacle avoidance in all three dimensions while maintaining ease of operation through automated algorithmic processing.
3Ease of manufacture
If 2D Lidar devices are used, then cost-effectiveness is achieved, but 3D object space mapping capability deteriorates
Solution Approach 1:
The patent replaces physical Lidar hardware with a software-based visual SLAM system that uses onboard cameras. Instead of relying on expensive 3D Lidar devices, the system substitutes computer vision algorithms that process camera images to construct three-dimensional environmental maps, achieving both cost-effectiveness and accurate 3D mapping capability.
4Device complexity
If manual warehouse management is used, then system simplicity is achieved, but operational efficiency and accuracy deteriorate
Solution Approach 1:
The patent implements autonomous UAV-based inventory management that performs warehouse tasks independently without continuous human intervention. The system self-navigates using visual odometry, autonomously captures inventory images, and automatically processes data, enabling the warehouse management system to serve itself and dramatically improving operational efficiency while maintaining manageable complexity through automated workflows.
Data Source
AI summary
An improved UAV system and methods for operation in an inventory management system. The methods include generating a three dimensional (3D) map and estimating a position and orientation of the UAV based upon this map; autonomously navigating the UAV in the environment by using the generated 3d map in conjunction with the position and the orientation of the UAV; performing static and dynamic obstacle avoidance in the environment using collision avoidance; and finding the optimal path from a source node to a destination node within the environment.