Mobile Robot Initialization Diagnosis for Stable Wake-Up Operation
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Solution Overview
Problem
Existing methods for initializing mobile robots are inadequate for ensuring stable cleaning operations without erroneous operations, as they fail to accurately diagnose and correct initialization states in real-time.
Innovation Solution
A method and system for diagnosing the initialization of mobile robots by executing an initialization diagnosis command, receiving diagnosis acquisition information, and calculating an initialization quality evaluation result to correct initialization values in real-time, ensuring stable operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional initialization methods are used when the mobile robot transitions from idle state to wake-up state, then the robot can start operation, but erroneous operations occur during cleaning operations due to inadequate initialization diagnosis
Solution Approach 1:
The system performs preliminary initialization diagnosis by executing specific commands to acquire sensor data and resource states before the robot begins its cleaning operation. This includes acquiring images from the camera module, LIDAR data from the LIDAR module, and sensor data from various sensors to verify proper initialization of all components before operation commences
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring sensor data and resource states during initialization, comparing acquired values against expected ranges, and providing diagnostic information about the initialization quality. This feedback loop enables the system to identify and correct initialization issues before they cause erroneous operations
2Measurement precision
If comprehensive initialization diagnosis is performed for all sensors and modules, then initialization quality can be accurately assessed, but the time and computational resources required increase
Solution Approach 1:
The initialization diagnosis is segmented into distinct modules corresponding to different robot components (camera module, LIDAR module, various sensors). Each module is diagnosed independently through specific commands, allowing the system to assess initialization quality of individual components without requiring exhaustive testing of the entire system, thus reducing overall initialization time while maintaining comprehensive coverage
Solution Approach 2:
The system performs partial initialization diagnosis by focusing on critical sensors and modules that have the greatest impact on operation stability. Rather than exhaustively testing every possible parameter, the system targets key initialization aspects such as camera image acquisition, LIDAR data collection, and sensor readings, achieving sufficient initialization quality assessment with reduced time investment
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
The method enables precise diagnosis of various resources and sensor values, allowing for real-time correction of initialization parameters, thereby ensuring stable operation and preventing erroneous operations of the mobile robot.
Implementation Method 1
the base station includes an initialization diagnosis marker including a reflector which reflects at least some of incident optical signals again to be identifiable by a camera module or a Lidar module
Data Source
AI summary
The present invention provides a method and a system for initialization diagnosis of a mobile robot. The present invention comprises the steps, executed by at least one processor included in a mobile robot, of executing an initialization diagnosis command to cause an initialization operation to be performed, the initialization operation being necessary to determine an initialization quality when a diagnosis target module transitions from an idle state to a wake-up state; receiving diagnosis acquisition information including a response according to the initialization diagnosis command in the wake-up state of the diagnosis target module; and, by using a task mission to be performed by the mobile robot and the diagnosis acquisition information, calculating an initialization quality evaluation result value indicating the initialization quality of the diagnosis target module, and executing a response operation according to the initialization quality evaluation result value.