3D Localization Mapping Using Visual-Inertial SLAM
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems for three-dimensional localization and mapping in robotic navigation require external hardware and tracking systems, making them expensive, time-consuming to set up, and limiting their use in unprepared environments without GPS or other tracking systems.
Innovation Solution
A mobile device equipped with an inertial measurement unit (IMU) and a three-dimensional image capture device, combined with SLAM algorithms, enables self-contained three-dimensional localization and mapping, eliminating the need for external tracking systems by using inertial and optical sensors to determine position and orientation in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional systems use external hardware such as fixed-position laser trackers, motion capture cameras, or markers placed on surfaces, then three-dimensional scan data can be acquired, but the system becomes expensive, time-consuming to set up, and requires prepared environments
Solution Approach 1:
The patent extracts the localization and mapping functionality from external hardware systems and relocates it to the mobile device itself. The mobile device now carries its own sensors (IMU, depth camera, visual camera) and processing capabilities to perform SLAM autonomously, eliminating the need for external laser trackers, motion capture cameras, or environmental markers.
Solution Approach 2:
The mobile device performs self-localization and self-mapping using its own onboard sensors and processors. The device captures visual data and depth information, processes this data through SLAM algorithms, and determines its own position and orientation without requiring external tracking systems or prepared environments with markers.
2Measurement precision
If conventional systems require external tracking systems for self-localization in unprepared environments, then position and orientation data can be obtained, but the setup becomes very expensive and time consuming
Solution Approach 1:
The patent removes the external tracking system requirement by extracting the localization functionality into the mobile device. The device uses its own visual sensors and IMU to perform visual-inertial SLAM, obtaining position and orientation data without any external infrastructure setup.
Solution Approach 2:
The mobile device autonomously performs localization in unprepared environments using its onboard visual and inertial sensors. The SLAM algorithm processes sensor data in real-time to determine the device's position and orientation, eliminating the need for expensive and time-consuming external tracking system setup.
3Measurement precision
If conventional systems place dozens of reflective markers on object surfaces for scanning, then three-dimensional data can be captured, but the process becomes laborious and requires prepared environments
Solution Approach 1:
The patent eliminates the marker placement requirement by extracting the feature detection capability to the mobile device's visual sensors. The device captures images and uses computer vision algorithms to automatically detect and track natural features in the environment, removing the need for reflective markers on object surfaces.
Solution Approach 2:
The mobile device autonomously detects and tracks environmental features using its visual camera and processes images through SLAM algorithms to capture three-dimensional data. This self-service approach eliminates the laborious process of manually placing dozens of reflective markers on all objects to be scanned.
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
Enables accurate, real-time three-dimensional mapping and localization in any environment without external components, improving efficiency and reducing setup time, and allowing for robust six degrees-of-freedom tracking and object scanning.
Implementation Method 1
The mobile device includes an inertial measurement unit and a three-dimensional image capture device
Implementation Method 2
receive three-dimensional image data of the environment from the three-dimensional image capture device
Data Source
AI summary
A system configured to enable three-dimensional localization and mapping is provided. The system includes a mobile device and a computing device. The mobile device includes an inertial measurement unit and a three-dimensional image capture device. The computing device includes a processor programmed to receive a first set of inertial measurement information from the inertial measurement unit, determine a first current position and orientation of the mobile device based on a defined position and orientation of the mobile device and the first set of inertial measurement information, receive three-dimensional image data of the environment from the three-dimensional image capture device, determine a second current position and orientation of the mobile device based on the received three-dimensional image data and the first current position and orientation of the mobile device, and generate a three-dimensional representation of an environment with respect to the second current position and orientation of the mobile device.