External Camera Robot Navigation in Crowded Indoor Spaces
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Solution Overview
Problem
Existing methods for driving robots in crowded areas, such as residential or shopping malls, face challenges in precise navigation due to limitations in simultaneous localization and mapping (SLAM) techniques, leading to inaccuracies in delivery tasks.
Innovation Solution
A method utilizing external camera modules installed inside or outside buildings to provide additional image-based information for controlling robot movement, enhancing navigation precision through a communication unit, drive-information acquiring unit, and control unit that generates instructions for precise positioning based on external images and sensing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If SLAM technique is used for robot navigation in crowded areas, then the robot can perform autonomous movement, but the navigation precision deteriorates due to inability to properly localize and map in crowded environments
Solution Approach 1:
The patent introduces external camera modules as intermediary devices installed in the environment to capture images of the robot. These external cameras serve as mediators between the robot's navigation system and the crowded environment, providing reliable visual data for localization that overcomes the limitations of onboard SLAM sensors in cluttered spaces
Solution Approach 2:
The patent transitions from relying solely on onboard sensors to incorporating external imaging resources from different spatial positions and perspectives. By utilizing camera modules installed at multiple locations in the environment, the system gains additional dimensional information about the robot's position that complements and enhances the SLAM-based navigation
2Measurement precision
If multiple external camera modules are deployed to improve navigation precision, then the robot positioning accuracy is improved, but the device complexity increases due to additional communication and control systems
Solution Approach 1:
The external camera modules serve multiple functions: they capture images of the robot for localization, provide visual data for navigation guidance, and enable communication between the robot and the environment. This multi-functionality reduces the need for separate specialized devices, thereby managing system complexity while maintaining high positioning accuracy
Solution Approach 2:
The system implements a feedback mechanism where external camera modules continuously capture robot images, the control server analyzes these images to determine robot position and generate guidance instructions, and the robot adjusts its movement accordingly. This closed-loop feedback system enables precise navigation through coordinated interaction between multiple components rather than requiring overly complex individual elements
Data Source
AI summary
Disclosed herein are a method for driving a robot based on an external image, and a robot and a server implementing the same. In the method, and the robot and server implementing the same, drive of a robot is controlled further using external images acquired by camera modules installed outside the robot. To this end, a robot according to an embodiment of the present disclosure includes a communication unit configured to communicate with external camera modules acquiring external images including the robot that is being driven, a drive-information acquiring unit configured to acquire driving related information at the time of driving the robot, a driving unit configured to drive the robot, and a control unit configured to control the driving unit using external information including the external images received from the external camera modules and the driving related information.