Autonomous Vacuum Cleaner 3D Mapping for Under-Obstacle Navigation
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Solution Overview
Problem
Autonomous-traveling vacuum cleaners face reduced cleaning efficiency due to inaccurate map generation when navigating under obstacles like beds or tables, as the camera captures only the lower surface, leading to lower accuracy in travel routes and map generation.
Innovation Solution
The vacuum cleaner employs a camera to capture images in its travel direction, a distance calculator to determine object distances, and a self-position estimator to generate three-dimensional maps, allowing for improved map accuracy and autonomous navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the camera captures images only in the forward traveling direction, then the device complexity is reduced, but the map generation accuracy deteriorates when navigating under obstacles
Solution Approach 1:
The patent transitions from two-dimensional forward-only image capture to three-dimensional omnidirectional image capture by adding cameras on the left and right sides. This dimensional expansion enables the system to capture obstacles and spatial relationships in all directions, resolving the accuracy deterioration when navigating under obstacles while maintaining manageable device complexity through modular camera integration.
2Productivity
If the vacuum cleaner travels under obstacles like beds or tables, then the cleaning coverage is improved, but the map generation accuracy deteriorates due to limited camera view
Solution Approach 1:
By adding lateral cameras on the left and right sides, the system gains three-dimensional spatial awareness that enables accurate mapping even when positioned under obstacles. This omnidirectional view allows the vacuum cleaner to capture the full extent of obstacles and navigate underneath them while maintaining high map generation accuracy.
Solution Approach 2:
The omnidirectional camera system serves multiple functions simultaneously: it captures forward, backward, left, and right views for comprehensive mapping, detects obstacles in all directions for safe navigation, and enables the vacuum cleaner to operate in previously inaccessible areas like under furniture, thereby achieving universal cleaning capability across diverse environments.
3Measurement precision
If three-dimensional data is collected from multiple directions, then the map generation accuracy is improved, but the device complexity increases due to additional cameras and processing
Solution Approach 1:
The patent implements three-dimensional data collection by strategically positioning cameras on the front, back, left, and right sides of the vacuum cleaner. This spatial arrangement captures omnidirectional images that, when processed together, generate accurate three-dimensional maps and depth information, achieving high measurement precision through controlled dimensional expansion.
Data Source
AI summary
A vacuum cleaner includes a main casing, a driving wheel, a camera, a distance calculation part, a self-position estimation part, a mapping part, and a controller. The driving wheel enables the main casing to travel. The camera is disposed on the main casing to capture an image in traveling direction side of the main casing. The distance calculation part calculates a distance to an object positioned in the traveling direction side based on the captured image. The self-position estimation part calculates a position of the main casing based on the captured image. The mapping part generates a map of a traveling place by using three-dimensional data based on calculation results by the distance calculation part and the self-position estimation part. The controller controls an operation of the driving wheel based on the three-dimensional data of the map generated by the mapping part, to make the main casing travel autonomously.