Flying Digital Assistant Control via Smartphone Gestures
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Solution Overview
Problem
Current UAV systems for image and video capture require piloting expertise and are prone to crashes due to pilot error, as they rely on direct control methods similar to traditional aircraft, lacking intuitive and user-friendly interaction paradigms.
Innovation Solution
The development of a Flying Digital Assistant (FDA) system that allows user interaction through a portable multifunction device (PMD), utilizing localization and navigation systems, including GPS, Wi-Fi, cellular, and computer vision, to enable indirect control of UAVs using paradigms like virtual camera, drawn paths, touch to focus, and scripted shots, allowing for autonomous image and video capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If direct control methods similar to traditional aircraft are used, then the UAV can be controlled with precise maneuverability, but the system requires piloting expertise and is prone to crashes due to pilot error
Solution Approach 1:
The patent introduces an intermediary control system that translates simple user gestures into complex UAV flight commands. The gesture recognition system acts as a mediator between the user and the UAV, interpreting natural hand movements and converting them into appropriate flight maneuvers, thereby eliminating the need for traditional piloting expertise while maintaining reliable control
Solution Approach 2:
The patent replaces traditional mechanical control interfaces (joysticks, switches, and physical controls) with a gesture-based recognition system. This substitution uses computer vision and machine learning algorithms to detect and interpret user gestures, replacing the mechanical interaction paradigm with a cognitive one that is more intuitive and less error-prone
2Ease of operation
If gesture recognition is used for control, then the ease of operation is improved, but the device complexity increases due to sensors and processing requirements
Solution Approach 1:
The UAV system performs self-calibration and adaptive learning of gesture patterns without requiring external configuration. The gesture recognition system automatically adapts to different users and environments through continuous learning, reducing the need for manual setup and calibration procedures while maintaining high recognition accuracy
Solution Approach 2:
The gesture recognition system is designed to work across multiple UAV models and control scenarios using a unified algorithmic framework. The same core technology serves various functions including flight control, camera operation, and navigation, reducing overall system complexity by avoiding the need for separate specialized systems for each function
Data Source
AI summary
Methods and systems are described for new paradigms for user interaction with an unmanned aerial vehicle (referred to as a flying digital assistant or FDA) using a portable multifunction device (PMD) such as smart phone. In some embodiments, a user may control image capture from an FDA by adjusting the position and orientation of a PMD. In other embodiments, a user may input a touch gesture via a touch display of a PMD that corresponds with a flight path to be autonomously flown by the FDA.