Image-Guided Mobile Display Alignment for User Tracking
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Solution Overview
Problem
Autonomous mobile devices (AMDs) face challenges in maintaining alignment with users due to limitations in their field of view and movement, leading to issues with displaying information and acquiring sensor data, especially when users move outside the camera's field of view or are backlit.
Innovation Solution
The AMD analyzes image data to determine the user's location and physical configuration, adjusting its position and orientation to maintain alignment by moving its display and camera to keep the user within the preferred area, using sensors to improve accuracy and avoid poor visual conditions like backlighting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the AMD uses a fixed field of view for camera and display, then the device structure is simple, but the user may move outside the viewing angle causing loss of information display and sensor data acquisition
Solution Approach 1:
The patent applies dynamics by making the camera and display moveable relative to the AMD chassis. The camera can pan and tilt independently, and the display can rotate and tilt, allowing the field of view and viewing angle to dynamically adapt to user position changes rather than being fixed
Solution Approach 2:
The system uses image data from the camera to detect user position and provides feedback to the control system. Based on this feedback, the system automatically adjusts the camera orientation and display angle to maintain optimal alignment with the user, creating a closed-loop control system
2Adaptability or versatility
If the AMD moves to follow the user, then the alignment with user is maintained, but the device consumes more energy and may collide with obstacles
Solution Approach 1:
The system segments the tracking function into two independent parts: the AMD chassis remains stationary while the camera and display independently adjust their orientations. This separation allows user tracking without requiring whole-device movement, reducing energy consumption and collision risk
Solution Approach 2:
The camera acts as an intermediary between the AMD and the user. By adjusting camera orientation and display angle rather than moving the entire device, the system achieves user tracking through intermediate component adjustments
3Measurement precision
If the AMD uses image data analysis to determine user position, then the alignment accuracy is improved, but the processing time and computational resources increase
Solution Approach 1:
The system replaces complex mechanical positioning systems with image-based optical detection. By using the camera to capture user position visually and analyzing image data computationally, the system achieves precise positioning without requiring complex mechanical measurement mechanisms
4Reliability
If the AMD maintains strict alignment with user, then the information display quality is improved, but the device cannot capture users in adverse lighting conditions like backlighting
Solution Approach 1:
The system dynamically adjusts the display orientation based on lighting conditions detected by the camera. When backlighting is detected, the display can rotate to face away from the light source, and the camera can tilt to find optimal viewing angles, allowing the system to adapt to adverse lighting rather than maintaining a fixed orientation
Data Source
AI summary
An autonomous mobile device (AMD) interacts with a user to provide tasks such as conveniently displaying information on a screen and moving with the user as they move. The AMD determines an area, or bounding box, of a user appearing within images obtained by a camera that is mounted on the AMD. A preferred area, with respect to the images, such as a center of the image, is specified to provide desired framing of images. As images are acquired by the camera, a difference between the bounding box and the preferred area is determined. Based at least in part on this difference, instructions are determined to move one or more of the cameras or the entire AMD to try and reframe the bounding box in subsequent images closer to the preferred area. Other factors, such as the user being backlit, may also be considered in determining the instructions.