Method of controlling mobile robot
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Solution Overview
Problem
Existing mobile robot technologies face challenges in accurately recognizing their position within a traveling area, especially under varying illumination conditions and in position jumping situations such as kidnapping, where traditional methods like infrared signals, laser sensors, and ultrasonic sensors are limited in cost and environmental detail extraction.
Innovation Solution
A method involving the generation of two basic maps under different illumination conditions, merging them to create a merged map, which allows for accurate position estimation by aligning border maps and using image information from the ceiling to select the current position, independent of illumination changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single basic map is generated under one illumination condition, then the map generation process is simple, but position recognition accuracy deteriorates when illumination conditions change
Solution Approach 1:
The patent merges multiple basic maps generated under different illumination conditions (illuminated and non-illuminated) into a single merged map. This allows the position recognition system to accurately identify locations regardless of illumination changes, resolving the contradiction between map generation simplicity and position recognition accuracy.
Solution Approach 2:
The patent changes the illumination parameter during map generation by creating separate basic maps under different illumination conditions. This parameter variation enables the system to handle illumination changes robustly while maintaining accurate position recognition.
2Ease of operation
If feature points are selected based on illuminated conditions, then feature extraction is straightforward, but position recognition reliability deteriorates when illumination changes
Solution Approach 1:
The patent creates a merged map that serves as a universal reference applicable under both illuminated and non-illuminated conditions. This universal map structure enables reliable position recognition across varying illumination environments while maintaining straightforward feature extraction procedures.
Solution Approach 2:
The patent performs preliminary action by pre-generating basic maps under different illumination conditions and merging them before actual position recognition occurs. This preparation ensures that the system is ready to handle illumination changes without compromising reliability during operation.
3Reliability
If traditional sensors (laser, ultrasonic) are used for position recognition, then position recognition in position jumping situations is possible, but device cost increases
Solution Approach 1:
The patent creates a virtual copy of the environment through image-based mapping, replacing the need for expensive physical sensors like laser and ultrasonic sensors. The merged map serves as a virtual representation that enables position recognition functionality without the high cost of traditional sensing hardware.
Solution Approach 2:
The patent substitutes mechanical/optical sensing systems (laser sensors, ultrasonic sensors) with an image-processing-based system. By using cameras and image analysis to create and compare maps, the system achieves similar position recognition capabilities without the complexity and cost of traditional sensor systems.
Data Source
AI summary
A method of controlling a mobile robot includes a first basic learning process of generating a first basic map based on environment information acquired in a traveling process, a second basic learning process of generating a second basic map based on environment information acquired in a separate traveling process, and a merging process of merging the first basic map and the second basic map to generate a merged map.