Drone Gesture Control via Vision-Based Recognition
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Solution Overview
Problem
Current aerial drone control systems lack the ability to effectively recognize and respond to user-made physical gestures for controlling drone movements and adjusting operations based on the user's activities, limiting their versatility and safety features.
Innovation Solution
A system that utilizes a drone camera to observe and recognize physical gestures made by the user, associating them with specific control commands and activity types, allowing the drone to perform corresponding maneuvers and adjust its operational mode accordingly, while also incorporating facial recognition and gesture-based authorization for enhanced control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional remote control methods are used for drone control, then the control system is simple and reliable, but the ease of operation is limited and versatility is reduced
Solution Approach 1:
The patent replaces traditional mechanical remote control systems with a vision-based gesture recognition system. The drone camera captures images of the user's hands, and image processing algorithms convert these visual inputs into control commands, substituting mechanical transmitters with optical sensing and computational processing.
Solution Approach 2:
The patent introduces an intermediary image processing system between the user and the drone control. The system includes a camera to capture hand gestures, image processing software to recognize patterns, and a command generation module to translate gestures into drone control signals, acting as a mediator that enhances ease of operation.
2Adaptability or versatility
If gesture recognition technology is added to enhance control versatility, then the adaptability and versatility improve, but the device complexity increases
Solution Approach 1:
The patent implements a universal control system where a single camera and image processing platform can recognize multiple types of gestures (hand movements, finger positions, palm orientations) and translate them into various drone control commands. This multi-functional approach allows one system to handle diverse control needs without requiring separate specialized devices.
Solution Approach 2:
The patent employs dynamic gesture recognition that adapts to different user behaviors and contexts. The system can learn and recognize new gesture patterns, adjust sensitivity thresholds, and modify control mappings based on usage patterns, making the system adaptable rather than static.
3Reliability
If activity recognition features are added to improve safety, then the reliability and safety features improve, but the measurement precision requirements and device complexity increase
Solution Approach 1:
The patent performs preliminary activity recognition by analyzing user gestures and context before executing drone maneuvers. The system identifies the user's intended activity (e.g., walking, running, stationary) and pre-adjusts control parameters and safety thresholds accordingly, preventing unsafe operations before they occur.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors recognized activities and adjusts drone behavior in real-time. When unsafe activities are detected (e.g., user falling, unexpected movements), the system provides feedback by alerting the user or automatically adjusting control parameters to maintain safety.
Data Source
AI summary
A method, system, and/or computer program product controls movement and adjusts operations of an aerial drone. A drone camera observes an aerial maneuver physical gesture by a user. The aerial drone then performs an aerial maneuver that correlates to the aerial maneuver physical gesture. The drone camera observes the user performing a physical action. One or more processors associate the physical action with a particular type of activity. A drone on-board computer adjusts an operation of an aerial drone based on the particular type of activity.