Autonomous traveling device
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Solution Overview
Problem
Conventional autonomous vacuum cleaners may get stuck or deviate from their intended route due to unaccounted obstacles or changes in the environment, as their maps do not accurately reflect the room's layout or dynamic changes in furniture and obstacle arrangements.
Innovation Solution
An autonomous traveler equipped with map generation, self-position estimation, and information acquisition means, which allows it to generate and update maps dynamically, perform self-position estimation, and adjust its route in real-time based on external information, enabling efficient navigation and cleaning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a traveling route is set only based on a stored map, then the autonomous traveler can navigate efficiently according to the pre-generated map, but the traveling may be disturbed by obstacles not indicated in the map or changes in the environment
Solution Approach 1:
The system dynamically switches between map-based navigation and real-time obstacle detection modes. The traveling route is not fixed but adapts based on environmental changes detected during navigation, allowing the system to maintain efficiency while responding to dynamic obstacles
Solution Approach 2:
The autonomous traveler continuously compares real-time sensor data with the stored map information, detecting discrepancies and adjusting the traveling route accordingly. This feedback mechanism ensures that the system can recover from deviations caused by unmarked obstacles while maintaining overall navigation efficiency
2Reliability
If the map generation process includes detailed interior and material information, then the autonomous traveler can avoid obstacles more effectively, but the map generation complexity and time increase
Solution Approach 1:
The system applies different levels of detail to different regions of the map based on cleaning priority and obstacle risk. High-priority areas with complex obstacles receive detailed mapping, while low-priority open areas use simplified representations, reducing overall map generation complexity while maintaining effective obstacle avoidance where needed
Solution Approach 2:
The system performs partial mapping focused on critical navigation information rather than complete detailed mapping of all surfaces. This selective approach provides sufficient obstacle avoidance capability without the full complexity of comprehensive interior and material documentation
3Reliability
If the autonomous traveler repeatedly operates to avoid obstacles, then it can prevent getting stuck, but the cleaning efficiency decreases due to time loss
Solution Approach 1:
The system performs preliminary route planning based on the stored map before actual traversal, identifying potential obstacle zones in advance. This allows the autonomous traveler to prepare avoidance strategies beforehand, reducing the need for repeated reactive maneuvers during cleaning operations
Data Source
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AI summary
Provided is a vacuum cleaner (11) capable of performing efficient autonomous traveling. The vacuum cleaner (11) includes a main casing, driving wheels, a map generation part (67), self-position estimation means (73), information acquisition means (75) and control means (27). The driving wheels enable the main casing to travel. The map generation part (67) generates a map indicative of information on an area. The self-position estimation means (73) estimates a self-position. The information acquisition means (75) acquires external information on the main casing. The control means (27) controls the operation of the driving wheels based on the map generated by the map generation part (67) to make the main casing autonomously travel. The control means (27) makes a search motion to perform when the information on the area at autonomous traveling is different from the information on the area indicated in the map generated by the map generation part (67).