Module 7.4 – UNSY 605

In order for unmanned systems to become a more viable option for many applications, the sense and avoid technology they operate must improve significantly.  The currently available options for unmanned systems do not provide effective enough detection and response capabilities to be viable options.  As a result, unmanned aerial vehicles (UAVs) present a severe risk for mid-air collisions with other aircrafts or stationary objects such as buildings.  Due to the risk of collision associated with flying UAVs, they must be flown within line of sight, which restricts their use for many applications at this time (Roden 2016).  The development of sense and avoid technology is advancing in two stages:  improved sense and avoid technology for better information relay to an operator and the development of completely autonomous sense and avoid technology (Roden 2016).  Both of these stages of development face major challenges, but there are some sensors available for operator-controlled UAVs.

            One popular avenue of improving sense and avoid sensor for UAVs has been to incorporate information from Automatic Dependent Surveillance-Broadcast (ADS-B) transponders.  There are two parts to an ADS-B, the ADS-B In and the ADS-B Out (Cincinnati Avionics 2016).  The ADS-B Out uses onboard GPS to transmit its position information to Air Traffic Control (ATC) while the ADS-B In receives position information on other aircraft carrying an ADS-B transponder (Cincinnati Avionics 2016).  uAvionix has designed several versions of their ADS-B transponders for commercial usage and the ping2020 ADS-B transceiver is perfect for use on small UAVs.  The ping2020 weighs only 20 grams and has a minimal power requirement at 500 mW (uAvionix 2016).  Aside from its small size, the ping2020 is optimal because it accomplishes both the ADS-B In and ADS-B Out functions (uAvionix 2016).  The ping2020 can detect objects within a 100 mile radius on two ADS-B In frequencies, 1090 MHz and 978 MHz (uAvionix 2016).  As for the ADS-B Out, the ping2020 transmits on the 978 MHz frequency (uAvionix 2016).  The only detail about the ping2020 is not ideal is the price.  Though I could not find a valid source for the price, I found one listing of the ping2020 for $1200, which is higher than desired when it comes to such a small component. 

            The ping2020 is a solid starting point for the first stage of sense and avoid technology development, but it is by no means a final solution.  The idea behind implementing an ADS-B transponder into a sense and avoid sensor is helpful, but it has its major faults.  The main issue is that in order to sense another aircraft that aircraft also has to be equipped with an ADS-B transponder.  The Federal Aviation Association (FAA) recently mandated that operate in U.S. National Airspace must be equipped with ADS-B by the year 2020, which means that the number of aircraft which are detectable by the ping2020 will be much higher (uAvionix 2016).  However, the ADS-B makes no improvements on the sense and avoid capabilities of stationary objects such as buildings or trees.  More than likely, small UAVs will not be operating in a high altitude environment for extended periods of time, which means that they will have to navigate obstacles presented by lower altitude areas.

            The bottom line for commercial small UAV operations in the future is that the discrimination capabilities of sense and avoid sensors must improve drastically.  Adding additional components, such as the ping2020 ADS-B, can help patch some of the issues for a short time.  But in the end, the sense and avoid sensors themselves have to become more effective to move forward in both operator-controller and autonomous UAV operations.

References

Cincinnati Avionics.  (2016). ADS-B 101:  what you need to know. Retrieved from http://cincinnatiavionics.com/ads-b-101-what-you-need-to-know/

Roden, M.  (2016). SkyTech Event:  UAV Conference & Exhibition. Retrieved from http://www.skytechevent.com/#!Sense-and-Avoid-The-Technology-to-Watch/c1leh/559bb52c0cf2361ae7868374

uAvionix.  (2016). PING-2020 ADS-B Transceiver.  Retrieved from http://www.uavionix.com/products/ping2020/

Module 6.4 – UNSY 605

The use and development of unmanned systems in the maritime environment has moved slowly when compared to its counterparts on the ground and in the air.  Typically, these maritime systems fall into two categories, autonomous underwater vehicles (AUVs) and unmanned surface vehicles (USVs).  In particular, AUVs face a number of challenges in their operational domain that have slowed their progress and widespread implementation.  However, Bluefin Robotics seems to be on the leading edge with AUV technology as their Bluefin-21, which has been purchased by the U.S. Navy, was inserted into search and rescue efforts for the Malaysia Airlines Flight 370 (Makinen 2014).  One of the main reasons that the Bluefin-21 was selected for use by the U.S. Navy are the capabilities and technology provided by the control station and its software.

Bluefin Robotics produces the Bluefin-9, -12S, -12D, -21, and HAUV AUVs all of which operate on the same Operator Tool Suite software package (General Dynamics 2016).  The software provides a Windows-based user interface which allows the operator to monitor and manage all aspects of the system and its mission (General Dynamics 2016).  There are three main functional modes provided by the Operator Tool Suite: Mission Planner, Dashboard, and Lantern.  As its name suggests, the Mission Planner tool allows for planning and verification of missions ranging from basic to complex plans (General Dynamics 2016).  The Dashboard tool provides an interface for vehicle testing and mission monitoring on a chart-based, operator-specified display (General Dynamics 2016).  Finally, the Lantern tool is used for post-mission sensor data display, analysis, and reporting (General Dynamics 2016).   

Since all of the systems produced by Bluefin Robotics are autonomous, there is not a great need for operator feedback within the system.  However, the system could be greatly improve if the technologies available in the Lantern tool were implemented in a real-time fashion.  Even though there is not an “operator” for an AUV, there is someone monitoring the progress of the system.  In the current system setup, the system monitor can only observe the status of the system components and track the progress of the system along its mission course.  Upgrading the Operator Tool Suite software to allow for real-time or near real-time sensor data display would provide great benefits for its mission accomplishment.  Having the capability to monitor sensor data immediately would allow for the system operator to determine if changes to the planned mission are needed. 

An example of when this ability would be beneficial is a search and rescue scenario similar to that of the Malaysia Airline Flight 370.  On the current system, the operator would have to wait until a search mission has been accomplished to determine if anything of worth was discovered.  If in the post-mission analysis, a significant discovery was made, the operator would then have to plan an entirely new mission to re-examine the area of interest.  Conversely, a system with the real-time sensor data display would provide the capability for the operator to make that same determination on the spot and adjust the current mission plan accordingly.  Creating a new Operator Tool Suite with this ability would increase the efficiency of search and rescue efforts significantly, reducing the burdens of time and cost.

Improving the Operator Tool Suite would certainly address an area of need in terms of conquering the hardships of AUV operations.  However, there are many other tasks that have to be tackled before the use of unmanned systems in the underwater domain becomes as pronounced as in the air and on the ground.  But each problem that is solved will make the successive progress a little easier.

References

General Dynamics.  (2016). Operator Software.  Bluefin Robotics.  Retrieved from http://www.bluefinrobotics.com/technology/operator-software/

Makinen, J.  (2014). Malaysia Airlines plane search goes underwater.  Los Angeles Times.  Retrieved from http://articles.latimes.com/2014/apr/14/world/la-fg-malaysia-bluefin-20140415