Robot without detection dead zone
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Solution Overview
Problem
Cleaning robots equipped with image sensors often experience detection dead zones, leading to potential collisions with obstacles during operation, resulting in noise and damage to furniture and devices.
Innovation Solution
The implementation of a cleaning robot that projects vertical light sections crossing each other in front of its moving direction, utilizing multiple light source modules and an image sensor to capture images and calculate object depth, thereby eliminating detection dead zones and enabling obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an image sensor is used as a detecting means in the cleaning robot, then the robot can detect obstacles, but detection dead zones are created in front of the moving direction leading to collision risks
Solution Approach 1:
The patent introduces a new detection dimension by projecting vertical light sections (parallel to moving direction) in addition to the conventional horizontal light sections. This creates a three-dimensional detection space that eliminates the dead zone in front of the robot, allowing obstacles directly ahead to be detected through their interaction with vertically projected light sections.
Solution Approach 2:
The detection space is segmented into multiple regions using separate light section projections: horizontal light sections cover lateral areas while vertical light sections cover the forward direction. This segmentation allows each light section group to specialize in detecting obstacles in specific spatial zones, collectively eliminating detection dead zones.
2Reliability
If multiple light source modules are added to eliminate detection dead zones, then obstacle detection is improved, but device complexity increases
Solution Approach 1:
The image sensor serves multiple functions: it detects obstacles interacting with horizontal light sections, detects obstacles interacting with vertical light sections, and can distinguish between different obstacle types (cliffs vs. regular obstacles) based on light section disruption patterns. This multi-functionality reduces the need for separate specialized sensors.
Solution Approach 2:
The patent combines horizontal and vertical light section projections into a unified detection system using a single image sensor. The processor integrates information from both light section orientations to comprehensively identify obstacles, merging multiple detection functions into one cohesive system rather than using separate independent detection systems.
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
This solution effectively prevents collisions by accurately detecting obstacles and cliffs, reducing noise and damage, and enhancing the robot's operational safety and efficiency.
Implementation Method 1
The first light source module is configured to project a first light section toward a moving direction. The second light source module is configured to project a second light section toward the moving direction
Implementation Method 2
The image sensor is configured to capture an image frame covering the first light section and the second light section
Data Source
AI summary
There is provided a cleaning robot including a first light source module and a second light source module respectively project a first light section and a second light section, which are vertical light sections, in front of a moving direction, wherein the first light section and the second light section cross with each other at a predetermined distance in front of the cleaning robot so as to eliminate a detection dead zone between the first light source module and the second light source module in front of the cleaning robot to avoid collision with an object during operation.