Cleaning Robot Escape Control at Floor Transition Traps
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Solution Overview
Problem
Intelligent mobile apparatuses, such as cleaning robots, often get trapped when transitioning between different types of ground surfaces due to differences in surface type and height, preventing them from completing their tasks.
Innovation Solution
The apparatus acquires ground medium attribute information when trapped, controls its movement to exit the trapping region in a different direction, and sets a target advancing direction and distance to re-enter, using sensors and controllers to navigate away from the trap effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the intelligent mobile apparatus continues to travel along the original direction after escaping the trapping region, then it may complete its cleaning task efficiently, but it risks re-entering the same trapping region and getting trapped again
Solution Approach 1:
Instead of continuing in the original direction which leads to re-trapping, the apparatus inverts its approach by selecting a different direction to re-enter the trapping region. This inversion of the original path prevents repeated entrapment while still allowing the apparatus to eventually complete its cleaning task by approaching the region from a safer angle.
2Reliability
If the intelligent mobile apparatus changes direction to avoid re-trapping, then the reliability of task completion improves, but the time required to complete the cleaning task increases
Solution Approach 1:
The apparatus applies partial action by making a directional adjustment only when necessary (upon detecting trapping conditions), rather than continuously changing direction. This selective application of direction change minimizes time loss while ensuring reliability by preventing re-trapping only when the risk is present.
3Device complexity
If the apparatus uses simple escape mechanisms, then the device complexity remains low, but the apparatus cannot effectively distinguish between different trapping situations and may fail to escape properly
Solution Approach 1:
The apparatus uses feedback from its sensors to detect trapping conditions and ground medium characteristics, then adjusts its escape strategy accordingly. This feedback loop allows the relatively simple escape mechanism to adapt to different trapping situations by making real-time directional adjustments based on sensor information about the environment.
Data Source
AI summary
An intelligent mobile device and a control method therefore are described. The method includes: acquiring, when the intelligent mobile apparatus is trap, first ground medium attribute information of a trapping region, where the first ground medium attribute information includes ground medium attribute information of the trapping region; and controlling, if the first ground medium attribute information matches target ground medium attribute information, the intelligent mobile apparatus to leave the trapping region and re-enter the trapping region in a direction different from a direction in which the intelligent mobile apparatus enters the trapping region.


