Autonomous Pet Exercise Drone With Adaptive Play Feedback
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Solution Overview
Problem
Existing toys and devices for domestic pets lack the ability to dynamically adapt and engage pets through a combination of movements and sounds, failing to effectively stimulate pets' natural play instincts.
Innovation Solution
An autonomous aerial vehicle (drone) system that recognizes pets and performs specific maneuvers and emits sounds to attract and engage pets, with a learning mode that adapts to individual pet preferences by capturing and scoring their reactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional static toys and devices are used for pets, then they provide basic play functionality, but they fail to dynamically adapt to individual pet preferences and effectively stimulate play instincts
Solution Approach 1:
The patent transforms static pet toys into dynamic interactive systems by implementing real-time motion detection, video analysis, and adaptive response mechanisms. The system continuously adjusts its behavior based on pet reactions, transforming fixed-functionality devices into dynamically adapting play companions that evolve with each interaction session.
Solution Approach 2:
The system incorporates multiple feedback loops including computer vision-based pet behavior analysis, audio reaction detection, and real-time adjustment of play patterns. Pet responses are captured through cameras and microphones, analyzed by AI algorithms, and used to modify subsequent interactions, creating a closed-loop adaptive system that learns from each pet's unique preferences.
2Productivity
If autonomous aerial vehicles perform complex maneuvers to engage pets, then play stimulation effectiveness increases, but energy consumption and operational complexity increase
Solution Approach 1:
The autonomous aerial vehicle implements periodic play patterns with varying intensity levels, alternating between high-energy maneuvers and lower-energy observation phases. The system uses periodic motion detection and engagement assessment to determine when to intensify activities and when to conserve energy, optimizing the balance between play effectiveness and energy consumption.
Solution Approach 2:
The system dynamically adjusts flight parameters including altitude, speed, and maneuver intensity based on real-time pet engagement metrics. When pet interest wanes or energy levels deplete, the system automatically modifies operational parameters to maintain effective engagement while reducing energy expenditure, utilizing adaptive parameter control rather than fixed high-energy patterns.
3Measurement precision
If the autonomous aerial vehicle uses multiple sensors and AI processing to recognize and respond to pets, then interaction accuracy and personalization improve, but computational requirements and system complexity increase
Solution Approach 1:
The computational system is segmented into distributed processing modules: onboard edge computing for real-time pet detection and basic response, cloud-based AI for complex behavior analysis and pattern recognition, and local control systems for immediate maneuver execution. This segmentation allows high measurement precision through comprehensive sensing while distributing computational complexity across multiple levels rather than concentrating all processing requirements in a single system.
Data Source
AI summary
A system and method employing an autonomous aerial vehicle programmed to stimulate a pet to engage in playful activities exercising the pet. The system is capable of executing a variety of rapid movements and emitting specific sounds designed to elicit reactions from the pet, such as barks, whines, and human utterances. In a learning mode, the system analyzes pet reactions to various stimuli. In a normal mode, it prioritizes movements and sounds that generate the most intense responses. The system includes safety measures to maintain a safe distance between the vehicle and the pet, ensuring that the vehicle automatically retreats if the pet comes too close. The system autonomously returns to its launch position when the pet disengages or when battery levels are low.