Pet Companion Robot Tracking for Centered Depth-of-Field Interaction
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Solution Overview
Problem
Current pet companion robots lack effective depth of field tracking and control mechanisms to interact with pets in a dynamic environment, limiting their ability to maintain optimal engagement and interaction.
Innovation Solution
A method for depth of field tracking and control of pet companion robots, utilizing a camera with control motors and a chassis with moving mechanisms, where the robot adjusts its position and camera angle to center the pet within its field of view, using AI algorithms to calculate and adjust the depth and height for optimal alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the pet companion robot uses basic movement and camera control without depth of field tracking, then the device complexity is low, but the interaction quality and engagement effectiveness deteriorate
Solution Approach 1:
The system continuously monitors the pet's position in the camera field of view and adjusts the robot's movement and camera orientation based on this feedback. The depth of field tracking algorithm calculates the pet's location and provides real-time feedback to the control system, enabling automatic adjustment of robot position and camera angle to maintain optimal engagement.
Solution Approach 2:
The robot autonomously tracks and centers the pet without requiring manual intervention. The depth of field tracking system automatically detects the pet's position, calculates the necessary adjustments, and executes the movement and camera control independently, making the interaction quality improvement self-sustaining.
2Reliability
If the robot continuously adjusts position and camera angle to maintain pet centering, then the engagement effectiveness improves, but the energy consumption increases
Solution Approach 1:
The depth of field tracking operates at optimized intervals rather than continuous maximum-power mode. The system periodically updates the pet's position and makes incremental adjustments, balancing engagement effectiveness with energy conservation by avoiding unnecessary continuous high-power operations.
3Measurement precision
If the robot uses simple movement control without depth of field tracking, then the device complexity is low, but the ability to maintain optimal engagement distance deteriorates
Solution Approach 1:
The depth of field tracking algorithm serves as an intermediary that processes camera image data to calculate the pet's position and distance. This intermediary layer translates simple camera observations into precise depth measurements, enabling accurate engagement distance control without requiring complex direct sensing hardware.
Data Source
AI summary
A method for depth of field tracking and controlling of a pet companion robot device to interact with a pet includes the steps of: locating a target pet within a field of view of the camera; drawing a minimum target rectangle around the target pet, with sides of the minimum target rectangle parallel with the corresponding sides of the field of view of the camera; locating a center point P of the minimum target rectangle. When P is located in quadrangles I and II, adjusting the pet companion robot device to the right to make P overlap with the vertical center line of the field of view of the camera; and when P is located in quadrangles III and IV, adjusting the pet companion robot device to the left to make P overlap with the vertical center line of the field of view of the camera.