Robot Return-to-Base Code Generation from Charging Base Signals
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Solution Overview
Problem
The development and debugging of robot return-to-base codes for different charging base designs are time-consuming and inefficient, requiring significant research and development effort due to varying infrared sensor configurations and signal distribution patterns.
Innovation Solution
An automatic generation method for robot return-to-base codes, where the robot collects and processes signal information and azimuth data using preset collection modes (traversal, national standard position, and middle signal region) to generate a return-to-base code, allowing the data processing device to configure the return-to-base flow information and generate a code corresponding to the charging base.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual development and debugging of return-to-base codes is performed for different charging base designs, then the code can be customized for specific sensor configurations, but the research and development time and energy consumption increase significantly
Solution Approach 1:
The system enables self-service by allowing the robot to automatically collect signal distribution data from different charging bases and generate corresponding return-to-base codes without manual intervention. The robot autonomously traverses the charging base, collects infrared signal information, and the data processing device automatically generates the code, eliminating the need for researchers to manually develop and debug codes for each charging base design.
Solution Approach 2:
The system handles different charging base designs by changing parameters rather than restructuring the entire development process. It collects signal distribution parameters (signal strength, azimuth, position) specific to each charging base and uses these parameters to generate appropriate return-to-base codes, allowing flexible adaptation to various sensor configurations without manual reprogramming.
2Adaptability or versatility
If manual development and debugging of return-to-base codes is performed for different charging base designs, then the code can be customized for specific sensor configurations, but the energy consumption increases
Solution Approach 1:
The system enables self-service by allowing the robot to automatically collect signal distribution data from different charging bases and generate corresponding return-to-base codes without manual intervention. The robot autonomously traverses the charging base, collects infrared signal information, and the data processing device automatically generates the code, eliminating the need for researchers to manually develop and debug codes for each charging base design.
Solution Approach 2:
The system replaces manual mechanical work (researchers physically debugging and writing code) with an automated data processing system. The data processing device automatically generates return-to-base codes based on collected signal distribution data, substituting human effort with computational processes that consume less energy and time.
3Productivity
If automatic generation method is implemented, then the research and development efficiency improves, but the system complexity increases
Solution Approach 1:
The system segments the return-to-base code generation process into distinct functional modules: signal collection module (robot collecting infrared signals), data processing module (processing collected data), and code generation module (generating return-to-base codes). This segmentation allows each module to be independently developed and tested, managing overall system complexity while maintaining high productivity.
Solution Approach 2:
The system introduces a data processing device as an intermediary between the robot and the final code generation. This intermediary collects raw signal data from the robot, processes it according to different charging base configurations, and generates appropriate return-to-base codes, simplifying the overall system architecture by centralizing the complex processing logic in a dedicated component.
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 method significantly improves research and development efficiency by automating the generation of return-to-base codes, enabling the robot to quickly adapt to different charging bases and enhancing universality, while reducing the need for manual programming and increasing accuracy in signal collection and code generation.
Implementation Method 1
a robot collects a guide signal which is sent by a charging base... the signal receiving device of the robot collects, in real time, the guide signal sent by the charging base
Data Source
AI summary
An automatic generation method for a robot return-to-base code includes the following steps that: on the basis of a preset signal collection mode, a robot collects a guide signal which is sent by a charging base and distributed within a preset range (S1); the robot transmits signal information and position information of the robot recorded when the guide signal is collected to a data processing device (S2); and the data processing device generates a robot return-to-base code corresponding to the charging base according to the received signal information and position information (S3). By means of the information collected by the robot in different modes, the data processing device automatically generates, according to the information, the robot return-to-base code corresponding to the charging base, so that research and development personnel do not need to delve into a robot return-to-base algorithm or write a specific return-to-base code.