Determining a condition of a window or door in a household
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Solution Overview
Problem
Existing floor cleaning robots struggle to accurately detect and differentiate between windows and doors, especially when they are partially obscured or in complex configurations, due to perspective issues and environmental interference, making it difficult to determine their open or closed states reliably.
Innovation Solution
A floor cleaning robot equipped with non-contact scanning capabilities, such as a camera or LiDAR, autonomously navigates to scan and learn the specific characteristics of individual access elements like doors and windows, storing this information for precise identification and state detection, allowing it to distinguish between various states like open, closed, or partially open, and optionally adjust their state if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If non-contact scanning is used to detect access elements, then detection range is improved, but detection precision deteriorates due to perspective distortion and environmental interference
Solution Approach 1:
The system transitions from 2D image analysis to 3D spatial understanding by incorporating depth information from LiDAR scanning. This allows the robot to distinguish between objects at different distances and angles, resolving perspective distortion issues while maintaining wide detection coverage of windows and doors.
Solution Approach 2:
The system introduces an intermediary processing layer that combines data from multiple sensors (camera and LiDAR) to create a fused representation of access elements. This intermediary processing step reconciles the conflicting requirements of wide detection range and high precision by integrating complementary information from both sensors.
2Reliability
If the robot scans all access elements continuously, then detection reliability is improved, but energy consumption increases
Solution Approach 1:
Instead of continuous scanning, the system implements periodic scanning at scheduled intervals combined with event-triggered scanning when state changes are detected. This reduces energy consumption while maintaining detection reliability by scanning only when necessary rather than continuously.
Solution Approach 2:
The system employs self-service mechanisms where the robot learns from previous scans and automatically adjusts its scanning behavior. Once access elements are identified and their states learned, the robot reduces scanning frequency for stable elements and focuses energy on elements showing change indicators, making the system energy-efficient while maintaining reliability.
3Measurement precision
If the robot learns individual characteristics of each access element, then detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system performs preliminary learning of access element characteristics during initial scans and updates the model gradually over time. By pre-processing and storing baseline characteristics of windows and doors, the robot reduces the complexity of real-time detection while maintaining high accuracy through prepared reference data.
4Productivity
If the robot operates close to the ground, then cleaning effectiveness is improved, but detection capability deteriorates due to limited field of view
Solution Approach 1:
The system merges the capabilities of multiple sensors (camera and LiDAR) to compensate for the limited field of view from ground level. By combining optical and spatial data, the robot achieves comprehensive detection capability while maintaining its low operating position for effective cleaning.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable and efficient detection of access element states with high accuracy, reducing the risk of unauthorized entry and environmental intrusion, while also performing its primary cleaning function, with minimal user intervention and efficient data management.
Implementation Method 1
A floor cleaning robot equipped with non-contact scanning capabilities, such as a camera or LiDAR
Data Source
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AI summary
An individual access element (115) to a room in a household (110) can be brought into an open and a closed state. A method (200) for detecting an individual state of the access element (115) comprises the steps of: determining a position (410) where an individual access element (115) is located in the household (110); non-contact scanning of the individual access element (115) while it is in a predetermined state; storing information about the individual access element (115) based on its scanning and state; capturing a further scanning of the individual access element (115) in the household (110); and detecting a state of the individual access element (115) based on the further non-contact scanning, the stored information, and the predetermined information.