Mobile Robot Image Filtering for Reduced Obstacle Recognition Latency
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Solution Overview
Problem
Conventional moving robots face challenges in accurately detecting and navigating around obstacles, particularly due to issues with image data quality under varying lighting conditions and speed, which can lead to inefficient cleaning and potential damage from collisions.
Innovation Solution
A moving robot equipped with a sensor unit, camera, and controller that analyzes image data for brightness and sharpness to filter and transmit only recognizable data to a server for obstacle identification, allowing the robot to adjust its path accordingly based on obstacle information received.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the moving robot transmits all photographed image data to the server for obstacle identification, then the obstacle recognition accuracy is improved, but the data transmission time and server load increase
Solution Approach 1:
The controller performs partial action by selectively transmitting only a subset of image data (specifically, image data meeting quality criteria such as brightness and sharpness thresholds) to the server, rather than transmitting all photographed image data. This reduces data transmission time and server load while maintaining sufficient obstacle recognition accuracy for safe navigation.
2Reliability
If the moving robot changes the traveling path immediately when an obstacle is detected, then the safety is improved, but the cleaning efficiency deteriorates
Solution Approach 1:
The controller performs preliminary action by identifying obstacles and preparing path adjustment strategies in advance, but delays the actual path change execution until necessary. This allows the robot to continue cleaning the current area efficiently while ensuring safety by making path adjustments only when obstacle proximity or collision risk becomes significant.
3Productivity
If the moving robot approaches closer to the obstacle before changing path, then the cleaning coverage is improved, but the collision risk increases
Solution Approach 1:
The controller uses feedback from continuous sensor monitoring of obstacle proximity and relative position to dynamically adjust the safe distance for path changes. When obstacles are detected, the robot approaches to maximize cleaning coverage while continuously receiving feedback on distance and position, making real-time adjustments to maintain safety margins and avoid collisions.
Data Source
AI summary
The present invention relates to a moving robot and a control method thereof, and includes a sensor unit configured to detect an obstacle located in a traveling direction; a camera configured to photograph the obstacle, when the obstacle is detected by the sensor unit; a controller configured to control a certain operation to be performed in accordance with the obstacle. The controller analyzes a plurality of image data of the obstacle inputted from the camera to determine whether the obstacle can be identified and filters the image data, transmits the filtered image data among the plurality of image data to the server through the communication unit, and controls the traveling unit in accordance with obstacle information received from the server. Hence, by transmitting only recognizable image, unnecessary data transmission is reduced, and accordingly, transmission traffic is reduced and the load of image processing of the server is reduced. As the load of the server decreases, the obstacle can be quickly determined, and accordingly, the moving robot can recognize the obstacle in a short time and determine the type of the obstacle to cope with, thereby performing the operation suitable for the feature of the obstacle, the cleaning area, or the surrounding environment.