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Crash controller for unmanned aerial vehicles.

IP.com Disclosure Number: IPCOM000239794D
Publication Date: 2014-Dec-02
Document File: 3 page(s) / 30K

Publishing Venue

The IP.com Prior Art Database

Abstract

A system and method for a crash controller (CC) for unmanned aerial vehicles (UAV) is disclosed. The CC system monitors airframe for impending crash and then tries to use remaining flight resources to influence airframe to crash land or safe land in preferred crash sites so as to minimize injury, loss of life and collateral damage.

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Crash controller for unmanned aerial vehicles .

Disclosed is a system and method for a crash controller (CC) for unmanned aerial vehicles (UAV). The CC system monitors airframe for impending crash and then tries to use remaining flight resources to influence airframe to crash land or safe land in preferred crash sites so as to minimize injury, loss of life and collateral damage.

As the skies get progressively more crowded with unmanned aerial vehicles, the odds

of a drone crashing to earth will drastically increase. Multiple systems and methods are disclosed that mitigate the consequences and minimize the chance of injury, loss of life, and property damage.

In an example embodiment, the system has the following components:
Parallel crash mitigation control system.


1.

Minimal control system that monitors airframe main control system and UAV


2.

operating characteristics.

Loss of control and/or potential crash detection.


3.

Module that detects main airframe control system has lost its operation capability. Embodiments may include

Heartbeat monitoring.


a.

Loss of remote operator control signals.


b.

Vertical descent speed thresholds surpassed.

UAV attitude thresholds surpassed.

Etc.

e.

Crash Site detection and prioritization:

Database of defined crash zones - areas set aside for sole purpose of safe crashing of UAV.

Mechanism to detect dynamically defined crash sites - these go in and out of existence, their location is broadcast per locale.

Database of lower risk areas - such as forests, lakes, oceans.

Image detection - downward facing camera and analytics to determine likely crash areas based on uniform images, or expanses where no movement is detected, etc.

Image detection - Cameras at selected crash sites that are signalled by the UAV at crash time, so crash characteristics can be studied by video and other metrics collected at crash site.

Payload Impact Assessment

A UAV will include a payload with different characteristics that can have components of the UAV (fuel, battery, frame composition) as well as cargo packages. Taking into account the payload will affect desirability of certain crash sites (i.e. try not to put potentially combustible content in a dry forest - put it in a pond ... or if the ground is covered with snow then put it in the snow instead of pond). Considerations:

a.

b. get wet, or won't survive hard impact but can get wet).


c.


d.


4.


5.

Dangerousness of the payload by impact location (wet/dry/hard/soft).

Potential damage of impact to payload (can survive a crash on land but can't

1


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c.

Environmental Considerations (best to crash downwind of people/habitat).

Value of payload - payload with a greater value than the UAV should prioritize crash sites where the payload would survive vs payload with less value than the UAV should prioritize crash site...