Robot Cleaner Multi-Sensor Navigation to Overcome Blind Spots
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Solution Overview
Problem
Conventional robot cleaners using two-dimensional spatial data face challenges in identifying objects in blind spots, leading to potential collisions or trapping, and three-dimensional image sensors have limitations due to narrow fields of view and data distortion issues.
Innovation Solution
A robot cleaner system that combines a three-dimensional image sensor, an optical sensor, and a gyro sensor, with the three-dimensional image sensor and optical sensor tilted at predetermined angles, to acquire and process spatial information, enhancing object detection and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a three-dimensional image sensor is used to acquire spatial information, then object detection capability is improved, but blind zones increase and measurement precision deteriorates
Solution Approach 1:
The patent divides the spatial detection task into multiple segments by using both a three-dimensional image sensor and a two-dimensional image sensor. Each sensor captures different types of spatial information (3D depth data and 2D visual data respectively), and their results are integrated to achieve comprehensive object detection that overcomes the blind zones of individual sensors.
Solution Approach 2:
The patent merges the detection results from the three-dimensional image sensor and the two-dimensional image sensor to create a more complete spatial understanding. By combining the depth information from the 3D sensor with the visual information from the 2D sensor, the system eliminates blind zones and improves overall object detection accuracy.
2Loss of information
If a three-dimensional image sensor is combined with the main body of a conventional robot cleaner, then spatial information acquisition is improved, but device complexity increases
Solution Approach 1:
The patent makes the image processing system universal by using both three-dimensional and two-dimensional image sensors that can handle multiple types of spatial information. This multi-functional approach allows the robot cleaner to acquire comprehensive spatial data (depth, width, height, and visual information) using a unified sensor system, reducing overall system complexity despite adding sensor types.
3Measurement precision
If data from three-dimensional image sensor and separate sensor is used to control driving state, then navigation accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent segments the navigation control process into distinct steps: first acquiring three-dimensional spatial information from the 3D image sensor, then acquiring two-dimensional visual information from the 2D image sensor, and finally integrating these segmented data types to make navigation decisions. This segmentation makes the complex processing manageable and systematic.
Solution Approach 2:
The patent uses an intermediary processing step that integrates the three-dimensional spatial information and two-dimensional visual information before controlling the driving state. This intermediary integration layer simplifies the overall processing complexity by combining multiple data streams into a unified navigation decision framework.
Data Source
AI summary
A robot cleaner is provided. The robot cleaner includes a three-dimensional image sensor, an optical sensor, a gyro sensor, and at least one processor configured to control a driving state of the robot cleaner based on image data acquired by the three-dimensional image sensor, optical data acquired by the optical sensor, and angular velocity data acquired by the gyro sensor, wherein the three-dimensional image sensor and the optical sensor are respectively arranged to be tilted by a predetermined tilting angle, and a tilting angle of the three-dimensional image sensor is smaller than a tilting angle of the optical sensor.