A plurality of autonomous cleaners and a controlling method for the same
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Solution Overview
Problem
Existing autonomous cleaners face challenges in recognizing the relative positions of each other without additional sensors, especially when they are far apart, leading to increased costs and inefficiencies in collaborative cleaning, particularly when using different cleaning maps for the same space.
Innovation Solution
The autonomous cleaners calibrate and unify their obstacle maps using a communication system to match coordinate systems, allowing them to recognize relative positions without additional position sensors, even when using different cleaning maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional position sensors such as ultrasonic waves and radar are mounted on autonomous cleaners to obtain relative positions, then measurement precision of relative positions is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses obstacle maps (digital copies of the physical environment) generated by each cleaner's own sensors to infer relative positions. Instead of directly measuring relative position with additional sensors, the system copies environmental information into map data structures and uses coordinate transformation to derive position relationships, thereby avoiding additional hardware while maintaining measurement capability
Solution Approach 2:
The patent replaces direct mechanical/sensor-based relative position measurement (ultrasonic waves, radar) with an information-processing approach using obstacle maps and coordinate transformations. The physical measurement system is substituted with a computational system that processes map data to determine relative positions, reducing hardware complexity
2Measurement precision
If high performance sensors capable of accurately recognizing positions are mounted on autonomous cleaners to work at large separation distances, then measurement precision is improved, but product cost increases
Solution Approach 1:
The patent uses copied environmental information in the form of obstacle maps to determine relative positions. Each cleaner creates a digital representation of its environment using standard sensors, and these map copies are exchanged and transformed to infer positions of other cleaners, eliminating the need for expensive high-performance sensors while maintaining accuracy
Solution Approach 2:
The patent introduces obstacle maps as an intermediary medium between cleaners for position recognition. Instead of cleaners directly measuring each other's positions using expensive sensors, the obstacle maps serve as an intermediate information carrier that enables indirect but accurate position determination through coordinate transformation
3Adaptability or versatility
If autonomous cleaners use different cleaning maps for the same space, then adaptability to different mapping methods is improved, but difficulty of detecting and measuring relative positions increases
Solution Approach 1:
The patent changes the coordinate system parameters (origin position, axis orientation, scale) of obstacle maps through transformation operations. By adjusting these parameters, the system can adapt different map types and coordinate systems to a unified reference frame, enabling relative position detection across diverse mapping methods without increasing complexity
Solution Approach 2:
The patent creates a universal coordinate transformation mechanism that can handle multiple types of obstacle maps and coordinate systems. The transformation function serves multiple purposes: unifying different map formats, establishing common reference frames, and enabling position comparison across heterogeneous data sources, thereby reducing detection difficulty while maintaining adaptability
Data Source
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AI summary
A plurality of autonomous cleaners and a control method thereof are disclosed. The present disclosure relates to a plurality of autonomous cleaners including a first cleaner and a second cleaner, wherein the first cleaner receives an obstacle map for a cleaning area from the second cleaner, performs calibration on the received obstacle map based on the coordinate system of its own prestored obstacle map, and transmits transformation data corresponding to the calibration to the second cleaner, and the second cleaner applies the transformation data to its own obstacle map, and recognizes the position coordinate corresponding to a wireless signal received from the first cleaner to generate a cleaning command.