UAV Hand-Gesture Landing for Safe Autonomous Recovery
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Solution Overview
Problem
Traditional UAV landing operations require significant user involvement and training, and are hindered by unsuitable ground conditions, necessitating a more automated and safe landing process.
Innovation Solution
An unmanned aerial vehicle (UAV) equipped with image and distance sensors that recognize hand gestures to autonomously hover and land on a user's hand, using a processor to execute instructions for gesture recognition and distance monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual remote control is used for UAV landing, then user control capability is maintained, but user training requirements and operational complexity increase significantly
Solution Approach 1:
The UAV performs self-landing by autonomously detecting hand gestures and executing landing sequences without requiring manual remote control operations. The system serves itself by using its own sensors to detect the operator's hand and automatically complete the landing process, eliminating the need for complex manual control procedures and extensive user training.
2Reliability
If traditional manual landing is used, then ground conditions can be assessed by user, but unsuitable ground conditions (soil, mud, rocks, water) still pose harm to UAV
Solution Approach 1:
The operator's hand serves as an intermediary platform for UAV landing. Instead of landing directly on potentially harmful ground surfaces like soil, mud, rocks, or water, the UAV lands on the hand which acts as a safe intermediate surface. This eliminates exposure to ground-related harmful factors while maintaining landing functionality.
3Ease of operation
If automated gesture recognition is implemented for landing, then user training requirements are reduced, but system complexity for gesture detection increases
Solution Approach 1:
The patent replaces complex mechanical control systems with optical sensing and image processing. Instead of using mechanical controllers and switches, the system uses cameras and computer vision algorithms to detect hand gestures, simplifying the user interface while leveraging sophisticated but integrated visual processing capabilities already present in modern UAVs.
Data Source
AI summary
An unmanned aerial vehicle (UAV) includes one or more processors, and a memory storing instructions. When executed by the one or more processors, the instructions cause the UAV to perform operations including: recognizing a first gesture of a hand; responsive to a recognition of the first gesture, moving the unmanned aerial vehicle to hover above the hand; detecting a distance between the unmanned aerial vehicle and the hand; responsive to a determination that the distance falls in a range, monitoring the hand to recognize a second gesture of the hand; and responsive to a recognition of the second gesture, landing the unmanned aerial vehicle on the hand.