OpenROV: A UMS for Everyone!

OpenROV is an open-sourced remotely operated miniature submarine aimed at making underwater exploration and education cheap and accessible to everyone.  The developers behind the project are do-it-yourself (DIY) enthusiasts Eric Stackpole, David Lang, and Matteo Borri.  The project was introduced on the Kickstarter website in 2012 in an effort to raise $20,000.  The project exceeded its Kickstarter funding goal by $91,622, and in 2013 ended its funding campaigns with over $1.3 million.  It was not until late 2013 that OpenROV v2.6 began to take orders on the OpenROV website.  It is expected that OpenROV v2.7 will become available in 2015.  

OpenRov

OpenROV is not the next generation of military UMS.  It does not use state of the art sensors, processors, or navigation systems.  It does not reach incredible depths nor does it maneuver at high speeds.  However, OpenROV is inexpensive.  The OpenROV Kit currently retails for $849.  It is easily obtainable by educational institutions and individuals with an interest in exploring.

OpenROV v2.6 is small, with dimensions of 15cm x 20cm x 30cm.  Eight C batteries provide approximately 1.5 hours of runtime.  The onboard processor is a low power, open-sourced, Linux based, BeagleBone Black.  It connects to a standard PC via a 100 meter tether cable.  It has an onboard high definition wide-angle camera with a tilt function, and LED lighting for low-light environments.      

            OpenROV represents the future of UMS because its low price significantly reduces the barrier to entry for underwater exploration.  The exploration of underwater environments is no longer limited to governments, large corporations, or researchers with large grants.  The OpenROV website has dozens of examples of how the platform is employed all over the world.  A middle school class in Hawaii purchased an OpenROV to study coral health after hurricanes.  A concerned citizen in Seattle used an OpenROV to help show that the city was dumping millions of gallons of untreated sewage and storm water into the cities waterways.  The city of Sydney, Australia hosted an open lab/hackerspace to innovate OpenROV solutions in the protection of marine life.  Portugal used an OpenROV to conduct a study of biological invasions by non-indigenous species.  The uses for OpenROV are endless.

            The open-sourced community allows OpenROV users and developers to share code, ideas, and answer technical questions.  Modifications are commonplace in the open source community.  The BeagleBone Black contains 2 x 46 pin headers, which allow the connection of third party digital sensors.  Code found in the OpenROV online repositories can bring third party sensors to life, or they can provide insight for users to do their own programming.  Further, 3D printing has been used in physical modifications.  Modifications allow the platform to operate outside of its initial design.

           

OpenRov Breakdown

OpenROV can interface with a computer by way of a LAN connection and a modern web browser.  Once the OpenROV is connected to a computer via LAN cable, its IP address is entered into a web browser and connectivity is achieved.  The operating system of the computer is not a factor, meaning it can be Windows, Linux, OSX, or anything else.  Users may choose to configure video game style controllers for easy operation.

            OpenROV gives tinkerers a platform to inexpensively experiment and solve underwater problems.  The lessons learned from OpenROV might one day be able to provide cost saving insight into the development of more expensive military UMS.  I believe that opening UMS to everyone is the future of UMS technology.    

References

Chung, Philip (2014).  OpenROV.  [ONLINE]  Available at: 

http://scinipenguin.mlml.calstate.edu/?p=938.  [Last Accessed 07 November 2014].

OpenROV (2014). Underwater Exploration Robots. [ONLINE] Available at: 

http://www.openrov.com/.  [Last Accessed 07 November 2014].

GPS-Free Robotic Explorers

The Institution of Engineering and Technology (IET) released an article on September 25, 2015 titled, “Robotic Explorers”.  The article summarizes a recent research paper titled “Multi-UAV-Based Stereo Vision System Without GPS for Ground Obstacle Mapping to Assist Path Planning of UGV”.  Jin Hyo Kim, Ji-Wook Kwon, and Jiwon Seo at the Yonsei University in Incheon, Korea authored the research paper.  The article and paper discuss an Unmanned Ground Vehicle (UGV) navigation technique that does not rely on a Global Positioning System (GPS) signal or other expensive navigation equipment.  The technique pairs a UGV with Unmanned Arial Systems (UASs) in the form of multicopters to provide imagery to the UGV aiding in the calculation of an optimum route.  

The agents of the prototype UGV/UAV cooperative system.

Decreasing UGVs dependency on GPS can increase their overall reliability.  The Defense Research Projects Agency (DARPA) understands the benefits of GPS free navigation and has funded five projects which include Adaptable Navigation Systems (ANS), Microtechology for Positioning, Navigation, and Timing (Micro-PNT), Quantum-Assisted Sensing and Readout (QuASAR), and the Program in Ultrafast Laser Science and Engineering (PULSE).  While the DARPA projects are ambitious, the solution offered by IET is low cost and relies on off the shelf technology.

The cooperative UGV/UAS uses multicopters equipped with off the shelf cameras for UGV path planning.  The cameras extrapolate terrain depth information without the use of Light Detection and Ranging (LIDAR), radar, or sonar.  LIDAR, radar, and sonar are limited to line-of-sight and cannot perceive objects behind obstacles.  This limits the path planning of UGVs.

The proposed UGV/UAS system “uses stereo-vision depth sensing to provide the obstacle map, and other image processing techniques to identify and track all the agents in the system, relative to each other and the environment, so GPS information is not needed”  (IET, 2014).  The stereovision mentioned is sometimes referred to as computer stereovision and is the extraction of 3D information obtained by (in this case) Charged Coupled Device (CCD) cameras.  The extracted information compares the images taken from two vantage points, resulting in depth information.  The system uses two multicopters to provide two vantage points.  

All testing of the corporative UGV/UAS has been conducted in laboratory settings.  During trial testing, the system was able to detect and avoid 42 obstacles in a series of seven tests.  However, the system detected 17 false alarms.  False alarms occur when the system detects obstacles that do not exist.

The article does not mention field tests of the cooperative UGV/UAS.  Field-testing will surely present many challenges.  Adverse weather conditions such as rain, snow, high winds, or sandstorms may limit the CCD computer stereovision system.  Further, the ground vehicles will be limited to the accessibility of the UAS.  Tunnels, caves, and forests will limit the UGV/UAS line of sight relationship. 

The cooperative UGV/UAS system shows promise for future application.  The importance of cost savings in UGVs is high.  According to the United States Department of Defense (DOD) “Unmanned Systems Integrated Roadmap, FY 2013-2038”, UGVs are expected to receive less funding than all other types of Unmanned Systems (USs).  However, the demand for military UGVs is high.  Applications of military UGVs will range from Explosive Ordnance Disposal (EOD); Chemical, Biological, Radiation, Nuclear (CBRN); engineering, logistics, transport; Intelligence, Surveillance, Target Acquisition, and Reconnaissance (ISR); and command and control.  In order for the DOD to meet the future demand for UGVs, cost effective measures such as the proposed UGV/UAS in “Robotic Explorers” are needed to accomplish milestones.

References

Defense Advanced Research Projects Agency (2014).  Beyond GPS:  5 Next Generation Technologies For Positioning, Navigation and Timing (PNT). [ONLINE]  Available at:  http://www.darpa.mil/NewsEvents/Releases/2014/07/24.aspx.   [Last Accessed 01 Nov 2014].

Department of Defense (2013). Unmanned Systems Integrated Roadmap FY 2013-2038. [ONLINE]  Available at: http://www.defense.gov/pubs/DOD-USRM-2013.pdf.  [Last Accessed 01 Nov 2014].

Institute of Technology and Engineering (2014). Robotic Explorers.  [ONLINE]  Available at:  http://www.theiet.org/resources/journals/eletters/5020/robotic-explorers.cfm.  [Last Accessed 01 Nov 2014].

Kim, Jin Hyo; Kwon, Ji-Wook; and Seo, Jiwon (2014).  Multi-UAV-Based Stereo Vision System Without GPS for Ground Obstacle Mapping to Assist Path Planning of UGV.  [ONLINE]  Available at: http://media.proquest.com.ezproxy.libproxy.db.erau.edu/media/pq/classic/doc/3464536441/fmt/pi/rep/NONE?hl=&cit%3Aauth=Kim%2C+Jin+Hyo%3BKwon%2C+Ji-Wook%3BSeo%2C+Jiwon&cit%3Atitle=Multi-UAV-based+stereo+vision+system+without+GPS+for+ground+obstacle+...&cit%3Apub=Electronics+Letters&cit%3Avol=50&cit%3Aiss=20&cit%3Apg=1&cit%3Adate=Sep+25%2C+2014&ic=true&cit%3Aprod=ProQuest+Advanced+Technologies+%26+Aerospace+Collection&_a=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%3D&_s=CUIVr66MaiROeSvd6inROLM4BqI%3D.  [Last Accessed 01 Nov 2014].

sUAS Sense and Avoid

In order to safely operate an aircraft of any type, it is necessary to detect incoming obstacles such as birds, buildings, other aircraft, weather, etc.  Pilots in manned aircraft are able to visually search and assess the airspace around their aircraft.  However, due to latency and unwanted breaks in communication, Unmanned Aircraft Systems (UASs) flying beyond an operator’s line of sight cannot accurately search and assess their airspace.

ICAO Cir 328, Unmanned Aircraft Systems (UAS)

Many large UASs have been outfitted with Sense and Avoid (SAA) systems to fill this gap.  “SAA functions to protect against collisions with other aircraft as well as various other hazards” (Zeitlin, 2010).  SAA in large UASs commonly use information from onboard transponders, Automatic Dependent Surveillance – Broadcast (ADS-B), optical sensors, LIDAR, and Radar to autonomously avoid threats.  However, small UASs (sUASs) (55 pounds or less) are not commonly outfitted with SAA systems due to weight and power constraints.

RADAR Based Collision Avoidance for Unmanned Aircraft Systems (2013) is a doctorate dissertation by Allistair A. Moses, from the Daniel Felix Ritchie School of Engineering and Computer Science, University of Denver, which provides insight on sUAS SAA technology.  Moses demonstrates the feasibility of a self-contained radar based collision avoidance system that weighs 304 grams (0.670205 pounds).  The SAA system was outfitted on an Align TRex450 Helicopter with a flying weight of 900 grams (1.98416 pounds).

RADAR Based Collision Avoidance for
Unmanned Aircraft Systems

The power consumption of the SAA is 5.8 W, with an input voltage of 5.6 VDC.  Its transmit frequency is 10.5 GHz with a transmit bandwidth of 5MHz.  It has a transmit power of 0.4mW and utilizes Frequency Shift Keying Continuous Wave Modulation (FSKCW).  FSKCW is a square wave modulation that is used to reduce background noise caused by terrain.   

The entire SAA system was built from scratch except for the antenna. The SAA uses a custom radar suite capable of detecting other aircraft.  The radar uses micro Doppler signal acquisition and identification consisting of quadruple transmit receive modules.  “This allows for the ready implementation of what they describe as a ‘Reactive Collision Avoidance Algorithm’ wherein the host vehicle steers away from the quadrants with the highest returned signal energy” (Moses, 2013).   

University of Denver faculty advisor Dr. Matt Rutherford stated, “in our field tests we were able to detect and identify targets of the size roughly equivalent to UAV at about 100 meters or 300 feet”  (Spendergast, 2014).  Researchers at the university are continuing to work on increasing the SAAs range.  In my opinion, a 100-meter SAA range on low power system weighing just over half a pound is impressive.  It should be noted that this technology could be up scaled to the effect that a larger sUAS with a SAA drawing more power can result in a longer detection range.     

Reference

Moses, Allistair A. (2013). RADAR Based Collision Avoidance for Unmanned Aircraft Systems. [ONLINE] Available at: http://digitaldu.coalliance.org/fedora/repository/codu%3A66898/Moses_denver_0061D_10839.pdf/Moses_denver_0061D_10839.pdf. [Last Accessed 28 February, 2015].

Pendergast, Stephen (2014). DU2SRI Miniature Radar May Give SUAS Sense and Avoid. [ONLINE] Available at: e.g. http://www.microsoft.com. [Last Accessed 28 February, 2015].

Zeitlin, Andrew D. (2010). Sense & Avoid Capability Development Challenges. [ONLINE] Available at: http://ieeexplore.ieee.org.ezproxy.libproxy.db.erau.edu/stamp/stamp.jsp?tp=&arnumber=5631723&tag=1. [Last Accessed 28 February, 2015].

Ground Control Stations: The VCS-4586 and the DDMS

The Ground Control Station (GCS) I have selected for this weeks blog is the Vehicle Control System (VCS) 4586 (GCS software) paired with the UAV Factory’s Dual Display Mobile Station (DDMS) (GCS hardware).  The VCS-4586 is produced by Lockheed Martin CDL Systems.  The VCS-4586 is a software suite capable of running on a wide variety of standard computer hardware and on Windows, Linux, and Solaris operating systems.  The VCS-4586 GCS can provide control to UASs, UGSs, and UMSs.  For the purpose of this blog post, I will focus on UGS and UMS capabilities.

The VCS-4586 supports real-time sensor video and telemetry.  The user interface allows operators to view sensor video by clicking the icon tagged to the sensors geographical position.  The system supports analog NTSC and PAL video streams, along with digital MPEG-2 and H.265 streams. 

The VCS-4586 reduces the workload of mission management.  The user interface allows operators to chart UGS and UMS routes, manage targets, and plot restriction zones.  3-D representations of routes are visualized on the monitor, and terrain elevation is accounted for.  The vehicle management system “allows for multiple vehicle control from as little as one ground control operator workstation” (Lockheed Martin, 2015).  Navigation of multiple vehicles is accomplished through point and click.  The VCS-4586 has been used to operate UMSs such as the Meggitt Training Systems Canada Barracuda, Hammerhead, and the Vindicator.   It has also been used to operate the General Dynamics Canada FORESIGHT (UGS).

In my opinion, the VCS-4586 is a powerful GCS software solution.  Its ability to function with many different platforms making it valuable to governments and organizations operating many types of unmanned systems.  The H.265 video codec features powerful compression for streaming video at ultra high definition up to 8K.        

            Although the VCS-4586 will function on many hardware setups, I think it will complement the UAV Factory’s Dual Display Mobile Station (DDMS).  The DDMS is a portable GCS built with off the shelf parts.  The 1000 x 420 x 170 mm GCS weighs 18.9 kg.  It is centered on a Panasonic CF-31 Toughbook, and features a secondary display and a modular electronics compartment for the connection of a data link or other required hardware such as video recorders, data acquisition devices, or data storage devices.  The DDMS features two USB ports, one Ethernet port, two serial ports, two video inputs, one VGA port, on microphone input, and one audio output.

            The DDMS is built with an expeditionary mindset that features hard shell protective case and hot swappable lithium ion batteries capable of a 30-minute quick charge.  The DMMS has an accessory bag, making “it convenient to carry small components and accessories such as a joystick, mouse, wiring, antennas, [or] external GPS antenna” (UAV Factory, 2015).            

            In my opinion, there are not many drawbacks to the DDMS because it is easily upgradable due to its off-the-shelf design.  The UAV Factory does not mention if the case is waterproof.  A waterproof pelican case for the DDMS would help prevent potential damage.  

References:

Lockheed Martin (2015). Ground Control Operator Software for Unmanned Vehicle Systems. [ONLINE] Available at: http://www.lockheedmartin.com/content/dam/lockheed/data/ms2/documents/cdl-systems/LM%20CDL%20Systems_Brochure_August_2013.pdf. [Last Accessed 21 February, 2015].

Lockheed Martin (2015). VCS-4586 CAPABILITIES GUIDE. [ONLINE] Available at: http://www.lockheedmartin.com/content/dam/lockheed/data/ms2/documents/cdl-systems/VCS-4586%20CAPABILITIES%20GUIDE-August2013.pdf. [Last Accessed 21 February, 2015].

UAV Factory (2015). Portable Ground Control Station. [ONLINE] Available at: http://www.uavfactory.com/product/16. [Last Accessed 21 February, 2015 ].

Unmanned System Data Protocol and Format

This blog post will discuss the data format, protocols, and storage methods associated with the AR.Drone 2.0.  The AR.Drone 2.0 is a hobby UAS built by the Paris based Parrot Company.  Parrot is a public company whose revenues reached  $272,691,500 USD in 2011.  ARS Technica has reported that over half a million AR.Drone units have been sold as of March 2013 (ARS Technica, 2013).  I specifically chose the AR.Drone 2.0 for this activity because it was my introduction to the hobby UAS world when I purchased one in 2012. 

The AR.Drone 2.0 uses two cameras to stream real-time video to smart devices.  The first camera is a forward-looking, wide angle, high definition 720p camera with a frame rate of 30fps.  The second camera is a downward pointing Quarter Video Graphics Array (QVGA) with a resolution of 320 x 240 pixels.  The QVGA camera has a frame rate of 60 fps and is used for groundspeed measurement.  Both cameras stream to a H.264 encoding base profile, and is transmitted to a smart device over a Wi-Fi b/g/n connection. 

            H.264 is also known as MPEG-4 Part 10-Advanced Video Coding (MPEG-4 AVC).  This is currently one of the most popular video compression formats.  However, the High Efficiency Video Codec (HEVC) H.265 may soon be replacing H.264.  Benchmark tests comparing H.264 and H.265 show that H.265 is capable of  “improving upon current streaming by cutting the required bitrate by up to 50 percent” (Tested, 2014).  I would recommend that Parrot consider upgrading their encoding base profile to H.265. 

            The AR.Drone 2.0 “can be controlled from any client device supporting the Wi-Fi ad-hoc mode”, (AR.Drone Developer Guide SDK 1.6).  The AR.Drone creates a Wi-Fi network allowing supported smart devices running flight control software to connect.  Wi-Fi 802.11b/g/n server has bandwidths of 22/20/40Mhz respectively, with outdoor ranges of 460/460/820 feet.  The 802.11n connection is ideal due to both its bandwidth and range.  The only Wi-Fi connection with a longer range is the 802.11a at up to 16,000 feet; however, its low data stream rate makes it impractical for streaming high definition video.

            Firmware data on the AR.Drone is the only data normally stored onboard.  The firmware can be updated through a USB 2.0 port on the bottom of the AR.Drone.  The AR.Drone 2.0 currently supports the connection of a USB 2.0 flash drive to store recorded video on the UAS.  AR.Drone users are encouraged to record video streamed to their smart devices via Android and iOS flight control applications.  I would recommend that Parrot consider using a small SD storage slot to record video onboard the AR.Drone.  The SD slot will not add significant weight, and it frees the USB for the possibility of adding aftermarket hardware.

            The AR.Drone 2.0 uses 6 miniaturized inertial measurement units to provide pitch, roll, and yaw measurements.  The sensors provide data to the processor for stabilization and tilt control.  Additionally, an ultrasound telemeter is used to determine altitude.  The firmware in the AR.Drone controls exactly how all of the sensory input is used.

References:

Cornish, David (2013). ESA Launches Drone App to Crowdsource Flight Data. [ONLINE] Available at: http://arstechnica.com/gadgets/2013/03/esa-launches-drone-app-to-crowdsource-flight-data/. [Last Accessed 07 February, 2015].

Fenlon, Wesley (2013). What You Should Know about The H.265 Video Codec. [ONLINE] Available at: http://www.tested.com/tech/web/453188-what-you-should-know-about-h265-video/. [Last Accessed 07 February, 2015].

Intel (2013). Real-Time CPU Based H.265/HEVC Encoding Solution with Intel Platform Technology. [ONLINE] Available at: https://software.intel.com/sites/default/files/white_paper_real-time_HEVC_encodingSolution_IA_v1.0.pdf. [Last Accessed 07 February, 2015].

Parrot (2011). AR.Drone Developer Guide SDK 1.6. [ONLINE] Available at: https://abstract.cs.washington.edu/~shwetak/classes/ee472/notes/ARDrone_SDK_1_6_Developer_Guide.pdf. [Last Accessed 07 February, 2015].

Parrot (2015). AR.Drone 2.0 Technical Specifications. [ONLINE] Available at: http://ardrone2.parrot.com/. [Last Accessed 07 February, 2015].