Acoustic Source Tracking for Autonomous Drone Investigation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current drone guidance systems rely heavily on visual data, making them cumbersome and less effective in low-visibility situations, and require significant weight and power resources, limiting their autonomy and mobility in monitoring spaces.
Innovation Solution
An acoustic monitoring system that utilizes a low-power, directionally-discriminating acoustic sensor coupled with an acoustic analysis engine to autonomously navigate drones to the source of acoustic energy, reducing the need for remote user control and minimizing hardware resources by processing audio signals against acoustic profiles stored locally and remotely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If visual data is used for drone guidance, then navigation capability is improved, but weight and power requirements increase
Solution Approach 1:
The patent replaces visual guidance systems with acoustic guidance systems. The drone uses acoustic sensors to detect and track acoustic signatures of targets, substituting the mechanical and computational complexity of visual processing with acoustic field-based navigation. This reduces the need for heavy cameras, image processors, and associated power systems while maintaining navigation capability through acoustic triangulation and signature recognition.
2Ease of operation
If visual data is used for drone guidance, then navigation capability is improved, but power consumption increases
Solution Approach 1:
The patent substitutes power-intensive visual processing systems with low-power acoustic sensing and processing. Acoustic sensors consume significantly less power than cameras and image processing units. The system processes acoustic signals to identify target signatures and navigate, reducing overall power consumption while maintaining autonomous navigation capability.
3Extent of automation
If autonomous guidance systems are added to drones, then autonomy is improved, but device complexity increases
Solution Approach 1:
The patent implements autonomous guidance through acoustic field interactions rather than complex visual processing systems. The drone autonomously detects acoustic signatures, triangulates source positions, tracks moving targets, and navigates to locations based on acoustic data. This approach achieves high autonomy with simpler hardware and processing requirements compared to visual-based autonomous systems.
4Loss of time
If visual-based autonomous navigation is implemented, then response time is reduced, but weight and power resources are increased
Solution Approach 1:
The patent replaces weight-intensive visual processing systems with acoustic-based navigation that achieves rapid response times. Acoustic sensors can detect and process target signatures in real-time with minimal computational overhead, enabling the drone to quickly respond to moving targets and changing environments without the weight penalty of sophisticated visual processing hardware.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances drone autonomy, reduces weight and power requirements, improves response time, and enables effective navigation in low-visibility conditions by allowing drones to navigate based on acoustic data, thereby improving their mobility and operational efficiency.
Implementation Method 1
receiving acoustic energy from the monitored space
Data Source
AI summary
A monitored space is monitored including the production of a first audio signal from received acoustic energy. The first audio signal is then processed against a whitelist of acoustic profiles and, based on lack of substantial correspondence with any of the acoustic profiles, a drone is navigated toward an apparent position of an apparent source. While in-flight, additional acoustic energy is received and a second audio signal is produced from the additional acoustic energy. The second audio signal is processed against the whitelist and, based on lack of substantial correspondence with any of the acoustic profiles of the whitelist, an investigate mode of the drone is initiated. The investigate mode includes notifying a remote monitor and supplying the remote monitor with an audiovisual feed. Responsive to a characterization by the remote monitor, an entry of the whitelist may be updated, added or replaced.