Cleaning Robot Charging Dock Search Using Map Contour Traversal Points
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Solution Overview
Problem
Existing cleaning robots face inefficiencies in finding the charging dock due to random roaming search methods, which can lead to prolonged search times when the dock's position changes or if the robot does not start cleaning from the dock.
Innovation Solution
The method involves obtaining a map of the scene, determining a map contour, identifying traversal points based on the map contour, and optimizing these points to efficiently search for the charging station in a predetermined order.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a random roaming search method is used to find the charging dock, then the robot can search for the dock anywhere in the environment, but the search efficiency is low and search time is prolonged
Solution Approach 1:
The robot performs preliminary actions by recording the charging dock position when it initially leaves the dock. This preliminary recording enables the robot to navigate directly to the dock later without needing to search, thereby improving search efficiency and reducing search time when the dock position remains unchanged.
Solution Approach 2:
The search process is segmented into two distinct modes: (1) direct navigation to recorded dock position when available, and (2) random roaming search only when the dock position has changed or is unknown. This segmentation allows the robot to use the efficient direct navigation method most of the time, improving overall productivity while minimizing time loss.
2Speed
If the robot records the charging dock position when leaving, then the robot can quickly return to the dock, but this method fails when the dock position changes or the robot didn't start from the dock
Solution Approach 1:
The system dynamically adapts its search strategy based on current conditions. When the recorded dock position is valid and unchanged, the robot uses direct navigation for fast return. When the dock position has changed or the recording is unavailable, the system automatically switches to random roaming search, ensuring adaptability while maintaining speed when possible.
Solution Approach 2:
The robot performs self-service by autonomously determining which search strategy to use based on its internal state (whether a dock position is recorded) and environmental conditions. The system independently handles both the fast return scenario and the adaptive search scenario without external intervention, improving both speed and versatility.
Data Source
AI summary
A method for docking a cleaning robot includes: obtaining a map of a scene where the cleaning robot is located, and a position of the cleaning robot in the map; determining a map contour where the position of the cleaning robot is located according to the map; determining a plurality of traversal points for searching for a charging station and a plurality of traversal areas corresponding to the plurality of traversal points according to the map contour; and searching for the charging station in the traversal areas corresponding to the traversal points according to a predetermined search order, until the charging station is found in the traversal areas, or the traversal areas corresponding to all of the traversal points have been searched.