Mobile Robot User Initialization With Guided Face Capture
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Solution Overview
Problem
Consumer-level robots lack effective initial interaction mechanisms with users, relying heavily on printed instructions and minimal user interaction, which limits their ability to adapt and provide personalized experiences.
Innovation Solution
The robot employs wireless network scanning, voice recognition, gesture recognition, and facial recognition technologies to establish initial interaction, allowing users to input network passwords and capture user data for future recognition, enabling cloud connectivity and personalized interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the robot uses traditional printed instructions for initial setup, then the device complexity is reduced, but the ease of operation deteriorates due to minimal user interaction and lack of personalized guidance
Solution Approach 1:
The robot performs self-introduction and guides the user through setup procedures autonomously, capturing user responses and adapting its behavior without requiring external instruction manuals or complex configuration interfaces
Solution Approach 2:
The robot captures user responses during initialization (such as name input) and uses this feedback to personalize subsequent interactions, creating an adaptive setup experience that improves ease of operation
2Measurement precision
If the robot captures multiple images during initialization, then the measurement precision of user recognition is improved, but the loss of time increases due to multiple orientation instructions
Solution Approach 1:
The robot captures multiple images of the user from different angles during the initial setup phase, storing these images for future recognition. By performing this action preliminarily, the robot avoids time-consuming image capture during actual recognition events
Solution Approach 2:
The robot efficiently guides the user through rapid orientation changes (left, right, forward, backward) to capture necessary images quickly, minimizing the time spent on initialization while ensuring sufficient recognition data is collected
3Adaptability or versatility
If the robot implements comprehensive user interaction during initialization, then the adaptability is improved, but the device complexity increases due to multiple sensors and processing requirements
Solution Approach 1:
The robot uses its existing camera and processor for multiple purposes: environmental scanning, user face capture, and gesture recognition, rather than adding dedicated separate systems for each function
Solution Approach 2:
The robot autonomously manages the complex initialization process by self-introducing, guiding users through orientation instructions, capturing images, and storing data without requiring complex external configuration systems
Data Source
AI summary
Initial interaction between a mobile robot and at least one user is described herein. The mobile robot captures several images of its surroundings, and identifies existence of a user in at least one of the several images. The robot then orients itself to face the user, and outputs an instruction to the user with regard to the orientation of the user with respect to the mobile robot. The mobile robot captures images of the face of the user responsive to detecting that the user has followed the instruction. Information captured by the robot is uploaded to a cloud-storage system, where information is included in a profile of the user and is shareable with others.