Systems and methods to command a robotic cleaning device to move to a dirty region of an area
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robotic cleaning devices, such as vacuum cleaners, often operate inefficiently due to limited awareness of their surroundings, leading to prolonged cleaning times and missed dirty areas, as they rely on trial and error to detect dirty regions rather than having a clear understanding of where dirtiest spots are.
Innovation Solution
A system utilizing cameras to collect and analyze images, identifying dirty regions through image recognition, and generating signals for robotic cleaning devices to move directly to these areas using GPS mapping, spatial analysis, or beacon triangulation, ensuring efficient cleaning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic cleaning devices operate using algorithms that focus on floor coverage, then the entire floor area is covered, but the cleaning time becomes very long and dirty areas may be missed
Solution Approach 1:
The system performs preliminary detection of dirty areas using cameras and image recognition algorithms before the robotic cleaner arrives. This advance identification allows the robot to navigate directly to detected dirty regions rather than searching randomly, significantly reducing cleaning time while ensuring no dirty areas are missed.
Solution Approach 2:
The patent introduces an intermediary detection system consisting of cameras and image processing algorithms that bridge the gap between random cleaning and targeted cleaning. This intermediary system identifies dirty areas and communicates their locations to the robotic cleaner, enabling efficient navigation and cleaning without requiring the robot to have inherent awareness of dirt locations.
2Measurement precision
If robotic vacuums use sensors to detect how much dirt is being cleaned up, then some dirt detection capability is achieved, but dirty areas are only discovered through prolonged trial and error
Solution Approach 1:
The patent replaces the mechanical sensor-based detection system with an optical detection system using cameras and image recognition algorithms. This substitution enables the system to visually identify and locate dirty areas from a distance, eliminating the need for the robotic vacuum to physically explore and discover dirty regions through trial and error, thereby dramatically reducing discovery time.
3Device complexity
If the robot has very limited awareness of its surroundings, then the device complexity is reduced, but the robot cannot identify which spots are the dirtiest
Solution Approach 1:
The patent divides the cleaning system into two separate functional components: a detection system (cameras and image processing) and a cleaning system (robotic vacuum). The detection system handles the complex task of identifying dirty areas, while the cleaning system focuses on executing the cleaning task. This segmentation allows the robot to maintain relatively simple onboard electronics while achieving sophisticated dirty area identification through the separate detection infrastructure.
Data Source
AI summary
In one aspect, a device includes a processor and storage accessible to the processor. The storage bears instructions executable by the processor to receive an image of an area from a camera, and to execute image recognition on the first image to identify a dirty region in the area. Based on the identification of the dirty region, the instructions are executable to generate a command for a robotic cleaning device to move to the dirty region for facilitating cleaning of the dirty region by the robotic cleaning device.