Robot Serving Navigation Using Table Callers for Accurate SLAM
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Solution Overview
Problem
Current autonomous driving robots face inefficiencies in Simultaneous Localization And Mapping (SLAM) due to excessive operation and data processing, requiring multiple sensing means for accurate results, which can lead to operation errors and increased costs.
Innovation Solution
A serving system where external callers, equipped with Ultra Wide Band (UWB) sensors and magnetic sensors, provide distance and direction information to the robot, allowing it to perform SLAM without the need for internal sensing means, thereby reducing operation and data processing time and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot uses multiple sensing means for accurate SLAM, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts the sensing function from the mobile robot and relocates it to external fixed apparatuses (callers) positioned at tables. The callers equipped with sensors capture images and measure distances, then transmit this data to the robot. This allows the robot to perform accurate SLAM without carrying multiple sensing means, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent introduces callers as intermediary devices between the robot and the environment. These callers act as mediators that capture environmental information (images, distance data) and relay it to the robot. This intermediary approach enables the robot to access precise environmental data without directly incorporating multiple sensors, thus resolving the contradiction between accuracy and complexity.
2Measurement precision
If the robot performs SLAM with multiple sensing means, then measurement precision is improved, but operation time increases
Solution Approach 1:
The patent extracts the time-consuming data acquisition and processing tasks from the robot and assigns them to external callers. The callers continuously capture images and distance information, preprocessing the data before transmission to the robot. This division allows the robot to receive ready-processed data, significantly reducing its operation time while maintaining high measurement precision through the callers' specialized sensing capabilities.
Solution Approach 2:
The callers perform preliminary actions by continuously capturing and preprocessing environmental data (images, distance measurements) before the robot needs it. This preliminary data preparation eliminates the need for the robot to perform time-consuming data acquisition and processing during its operations, thereby reducing loss of time while ensuring accurate SLAM through pre-processed high-quality data.
3Measurement precision
If the robot uses multiple sensing means for SLAM, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent extracts the sensing means from the robot and relocates them to external callers positioned at fixed locations (tables). Instead of equipping the robot with multiple expensive sensors, the system uses callers with sensing capabilities that remain stationary. This approach maintains measurement precision for SLAM while significantly reducing the quantity of sensing means required on the mobile robot, thereby lowering overall system cost.
Solution Approach 2:
The patent implements multiple callers at different table locations, each acting as a distributed sensing node. Rather than concentrating all sensing capabilities in one mobile robot, the system creates copies of sensing functionality across multiple fixed positions. This distributed approach provides comprehensive environmental coverage for accurate SLAM while using simpler, lower-cost sensing units at each location compared to a fully-equipped mobile robot.
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
This approach enables accurate and efficient SLAM for autonomous driving robots by offloading sensing tasks to external callers, reducing operation errors and maintaining low costs without harming humans, while allowing for precise location tracking and obstacle detection.
Implementation Method 1
The positioning sensor may be provided as an Ultra Wide Band (UWB) sensor
Implementation Method 2
a magnetic sensor for sensing whether a table with the caller rotates and the rotational angle thereof
Data Source
AI summary
A serving system using a robot may include a caller mounted on each of a plurality of tables, and a robot driving to a target table among the plurality of tables based on information received from the caller, and the robot may store information on the location of each of the plurality of callers, the size and shape of each of the plurality of tables, the location of the caller mounted on the table, and the rotational angle with respect to a baseline of the caller, and the caller may transmit to the robot information on the distance from the caller to the robot and the direction of the robot with respect to the caller during driving of the robot.