Collaborative Cleaning Robot Zone Assignment Based on Location Data
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Solution Overview
Problem
Existing cleaning robot systems face challenges in efficiently dividing and managing cleaning zones among multiple robots, leading to prolonged cleaning times and inefficient collaborative cleaning within a shared space.
Innovation Solution
A collaborative cleaning system that assigns individual cleaning regions to robots based on their location information, using processors to map and merge location data, and prioritize cleaning tasks, allowing robots to communicate and adjust their cleaning paths dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple cleaning robots are deployed to clean a large cleaning zone, then the cleaning coverage and productivity are improved, but the coordination complexity and time management become more difficult
Solution Approach 1:
The cleaning zone is divided into multiple sub-zones, and each cleaning robot is assigned to a specific sub-zone based on its location. This segmentation allows multiple robots to work simultaneously without complex coordination, as each robot independently cleans its designated area. The processor automatically determines the cleaning sub-zone for each robot, simplifying the division of labor.
2Productivity
If multiple cleaning robots operate in the same cleaning zone, then the cleaning productivity increases, but the cleaning time management and collision avoidance become more challenging
Solution Approach 1:
Before the cleaning operation begins, the processor pre-determines the cleaning sub-zone for each cleaning robot based on its initial location. This preliminary assignment of zones prevents robots from entering each other's paths, eliminating the need for real-time collision avoidance and ensuring efficient time management. Each robot knows its designated area in advance, preventing redundant cleaning and optimizing the overall cleaning time.
3Ease of operation
If cleaning robots autonomously determine their cleaning paths, then the ease of operation is improved, but the measurement precision of location and path planning becomes more critical
Solution Approach 1:
The processor acts as an intermediary that receives location information from cleaning robots and determines their assigned cleaning sub-zones. Instead of requiring robots to independently calculate complex paths with high precision, the processor simplifies the task by assigning specific sub-zones based on robot locations. This intermediary step reduces the measurement precision requirements for individual robots while maintaining autonomous operation.
Data Source
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AI summary
The disclosure relates to a moving apparatus for cleaning, a collaborative cleaning system, and a method of controlling the same, the moving apparatus for cleaning including: a cleaner configured to perform cleaning; a traveler configured to move the moving apparatus; a communicator configured to communicate with an external apparatus; and a processor configured to identify an individual cleaning region corresponding to the moving apparatus among a plurality of individual cleaning regions assigned to the moving apparatus and at least one different moving apparatus based on current locations throughout a whole cleaning region, based on information received through the communicator, and control the traveler and the cleaner to travel and clean the identified individual cleaning region. Thus, the individual cleaning regions are assigned based on the location information about the plurality of cleaning robots, and a collaborative clean is efficiently carried out with a total shortened cleaning time.