Mobile Robot User-Following Path Recovery After Tracking Loss
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Solution Overview
Problem
Mobile robots face challenges in determining an appropriate traveling path when the tracking of a user is interrupted due to increased distance, obstacles, or low image quality, which affects their ability to accurately recognize the user or obstacles.
Innovation Solution
A mobile robot equipped with a camera and processor that photographs its surroundings, detects the user, tracks the user's location, predicts the user's movement direction when tracking is stopped, and determines a traveling path based on this prediction to resume following the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the mobile robot uses a camera to track the user, then the robot can follow the user within the camera's vision field, but when the user moves out of the vision field or obstacles block the view, the robot cannot determine the appropriate traveling path
Solution Approach 1:
The system performs preliminary action by predicting the user's movement direction before the user actually moves out of the vision field. The processor analyzes the user's current movement trajectory and predicts future position, allowing the robot to prepare the traveling path in advance. This prevents complete loss of tracking when the user exits the camera view.
Solution Approach 2:
The patent introduces an intermediary mechanism - the prediction module that works between the camera detection system and the path planning system. When direct visual tracking fails, the prediction module provides intermediate information (predicted user position and direction) to maintain continuous path determination, bridging the gap between lost visual contact and successful path recovery.
2Measurement precision
If the mobile robot relies on image quality for user recognition, then accurate recognition is achieved under good lighting conditions, but when image quality is low, the robot cannot accurately recognize the user or obstacles
Solution Approach 1:
The system implements feedback by continuously monitoring image quality and tracking stability. When image quality degrades or tracking becomes unstable, the system activates prediction algorithms that use historical tracking data to compensate for poor current frame quality. This feedback loop allows the robot to maintain recognition accuracy despite varying image conditions.
Solution Approach 2:
The patent applies parameter changes by switching between different tracking strategies based on image quality parameters. When image quality is high, the system uses direct visual tracking. When image quality degrades, it transitions to prediction-based tracking using motion vectors and historical position data, effectively changing the operational parameters to adapt to poor imaging conditions.
3Reliability
If the mobile robot maintains continuous visual contact with the user, then accurate path following is achieved, but when the user moves beyond the camera's range, the robot loses tracking capability
Solution Approach 1:
The patent applies dimensionality change by transitioning from two-dimensional image plane tracking to three-dimensional space prediction. Instead of being constrained to the camera's 2D vision field, the system uses motion trajectories and spatial relationships to predict the user's position in 3D space, allowing path determination even when the user is outside the current camera view.
Data Source
AI summary
Provided are a mobile robot and a method of driving the same. A method in which the mobile robot moves along with a user includes photographing surroundings of the mobile robot, detecting the user from an image captured by the photographing, tracking a location of the user within the image as the user moves, predicting a movement direction of the user, based on a last location of the user within the image, when the tracking of the location of the user is stopped, and determining a traveling path of the mobile robot, based on the predicted movement direction of the user.