16964982. METHOD OF UPDATING MAP IN FUSION SLAM AND ROBOT IMPLEMENTING SAME simplified abstract (LG ELECTRONICS INC.)
METHOD OF UPDATING MAP IN FUSION SLAM AND ROBOT IMPLEMENTING SAME
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METHOD OF UPDATING MAP IN FUSION SLAM AND ROBOT IMPLEMENTING SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 16964982 titled 'METHOD OF UPDATING MAP IN FUSION SLAM AND ROBOT IMPLEMENTING SAME
Simplified Explanation
The patent application describes a method and robot for updating a map in fusion SLAM (Simultaneous Localization and Mapping) using two types of sensors. The robot is designed to update a first map with information acquired by a first sensor and estimate its current position using information acquired by a second sensor.
- The method involves updating a map in fusion SLAM using two types of sensors.
- The robot is configured to update a first map with first type information acquired by a first sensor.
- The robot also uses second type information acquired by a second sensor to estimate its current position.
- Fusion SLAM refers to the simultaneous localization and mapping technique that combines sensor data to create and update a map while estimating the robot's position.
Potential Applications
- This technology can be applied in various fields where accurate mapping and localization are crucial, such as robotics, autonomous vehicles, and drones.
- It can be used in indoor navigation systems to create and update maps of buildings or large facilities.
- The method can be implemented in search and rescue robots to accurately navigate and map disaster-stricken areas.
Problems Solved
- Traditional SLAM techniques often rely on a single type of sensor, which may not provide sufficient accuracy or coverage.
- By using two types of sensors, this method improves the accuracy and reliability of the map updates and robot localization.
- The fusion of sensor data allows for better mapping and localization in complex environments with varying conditions.
Benefits
- The use of two types of sensors enhances the accuracy and reliability of map updates and robot localization.
- The fusion SLAM technique enables real-time mapping and localization, which is essential for autonomous systems.
- This method can improve the efficiency and effectiveness of various applications, such as autonomous navigation, surveillance, and exploration.
Original Abstract Submitted
Disclosed herein are a method of updating a map in fusion SLAM and a robot implementing the same, the robot, which updates a map in fusion SLAM using two types of sensors, configured to update a first map with first type information acquired by a first sensor and to estimate a current position of the robot using second type information acquired by a second sensor.