Moving Robot Image-Based Cliff Detection Beyond Obstacles
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Solution Overview
Problem
Conventional robot cleaners face challenges in detecting cliffs beyond obstacles, leading to potential falls, and struggle with navigating spaces with varying floor heights, resulting in getting trapped.
Innovation Solution
The moving robot analyzes images around its body to detect the height of the floor surface beyond an obstacle, determining whether to climb the obstacle by calculating the height and depth of the floor surface, and adjusts its approach to enter obstacles vertically to avoid getting trapped.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a cliff sensor is provided in the bottom of the main body to detect cliffs, then the robot cleaner can recognize the existence of cliffs, but the robot cleaner must be close to the cliff or have its body positioned on the cliff to detect it, leading to frequent falls
Solution Approach 1:
The patent transitions from bottom-mounted cliff sensors to front-mounted cameras that capture images of the floor surface beyond obstacles. This dimensional shift allows the robot to detect cliffs at a distance before approaching them, rather than requiring contact or proximity detection from the bottom sensors.
Solution Approach 2:
The system performs preliminary cliff detection by capturing images of the floor surface beyond obstacles before the robot approaches. The controller calculates the depth of the floor surface in advance and determines whether it is a cliff, allowing the robot to avoid cliffs before they become a hazard.
2Adaptability or versatility
If the robot cleaner climbs a chassis obstacle to navigate between floors of different heights, then the robot can move between areas, but the robot may fall to the lower floor during direction changes or become trapped if the lower floor cannot be climbed from
Solution Approach 1:
The controller captures images of the floor surface beyond the chassis obstacle in advance and calculates the depth. Based on this preliminary assessment, the controller determines whether the floor beyond is safe to traverse or if the robot should avoid climbing the chassis, preventing falls and trapping situations before they occur.
Solution Approach 2:
The camera and image processing system serve as an intermediary between the robot and the obstacle. By analyzing images of the floor surface beyond the chassis and calculating depth, the system provides critical information that mediates the decision-making process, enabling safe navigation or avoidance of potentially hazardous obstacles.
3Measurement precision
If the robot uses optical sensors to detect obstacles and perform mapping, then the robot can identify terrain and obstacles, but the robot cannot determine the height of the floor surface beyond obstacles, leading to undetected cliffs
Solution Approach 1:
The patent replaces traditional mechanical/optical cliff sensors with a camera-based imaging system. The camera captures visual information of the floor surface beyond obstacles, and the controller processes these images to calculate depth and determine floor height, substituting mechanical sensing with optical imaging and computational analysis.
Solution Approach 2:
The image processing system acts as an intermediary that bridges the gap between visual detection and depth measurement. By capturing images and calculating the depth of the floor surface, the system recovers the height information that would otherwise be lost, enabling the robot to detect cliffs beyond obstacles.
Data Source
AI summary
The present disclosure analyzes the image around the main body, detects the depth of the floor surface and the height of the floor surface beyond the obstacle, and determines whether to climb the obstacle.