UNSY 605, Assignment 7.5, Sense and Avoid Sensor Selection

     Unmanned aerial systems’ (UAS) sensor systems for sense-and avoid (SAA) functions present a formidable challenge.  The system must provide a level of safety at least equal to that provided by a human operator’s SAA capabilities.  This threshold must be met for the Federal Aviation Administration (FAA) to approve of UAS operations in the National Airspace (NAS) and, ultimately, for the public’s approval.  A Group 2 category UAS is relatively small and light, restricting a SAA system to compact, lightweight, and power-efficient components.
    The Advanced Scientific Concepts (ASC) Peregrine 3D Flash laser detection and ranging (LIDAR) system is a suitable sensor for SAA functions on a Group 2 category UAS.  The Peregrine weighs only one pound and measures only 2 inches by 3 inches by 6 inches.  The LIDAR requires 24 watts of starting power with 13 watts for continued operation and operates at 20 Hertz.  The Peregrine features a 60 degree field of view (FOV) lens and a Class I eye-safe laser.  Figure 1 presents a view of the exterior of the Peregrine.

Figure 1.  The Peregrine 3D Flash LIDAR.

The sensor also features widely compatible support equipment and operating software.  The Peregrine can withstand environmental conditions that make it suitable for an aerial platform.  The maximum detection range of the LIDAR varies depending on laser power and the reflectivity of the detected object (“ASC”, 2015).  Tests by LIDAR technology enthusiasts have produced detection ranges of approximately 1,200 feet (400 meters) (LIDAR News Staff, 2015).
    The Peregrine LIDAR uses a solid state three-dimensional staring array.  By comparison, a LIDAR using a scanning array usually contains an oscillating mirror to sweep the laser pulses through an arc and an inertial measurement unit to measure the aircraft’s orientation.  These components ensure the position of each pulse is recorded to ensure accuracy in the data collected (Anderson et al., 2006). 
Figure 2 provides an example of a scanning array (Glennie et al., 2013).

Figure 2.  A example of a mirror and prism in a LIDAR scanning array.

The Peregrine does not require these moving parts to achieve similar results.  These properties allow for a reduction in size and weight of the overall system.  The lack of requirement for an inertial system to record orientation also means the Peregrine would be more forgiving of a carrying UAS’ maneuvers or light turbulence.  ASC’s product page (2015) explains that their LIDAR illuminates an area incorporating the FOV with a single 5 nanosecond pulse per frame.  The reflected laser light is captured in the form of three-dimensional point clouds and co-registered intensity data.  Resolution of 128 x 32 pixels can be achieved with a 4:1 aspect ratio.  Standard Ethernet ports and power connectors ensure the Peregrine is easily integrated into UAS platforms.
    The Peregrine 3D Flash LIDAR presents a SAA capability for independent operation.  SAA systems such as Automated Dependent Surveillance-Broadcast (ADS-B) have been recommended for UAS operations in the NAS (Marshall, 2013, p. 1-2).  However ADS-B relies on cooperation among aircraft and ground stations.  An aircraft without ADS-B installed will not be detected by the system.  ADS-B would also not be of any help during an encounter with a flock of large birds such as Canada geese.  A LIDAR such as the Peregrine would provide a very useful, independent SAA system to supplement ADS-B coverage.

References

Advanced Scientific Concepts (ASC).  Peregrine 3D Flash LIDAR Vision System [Product Sheet].  Retrieved from http://www.advancedscientificconcepts.com/products/Peregrine.html

Anderson, H., McGaughey, R., Reutebuch, S., Schreuder, G., & Agee, J.  (2006, July 31).  Website of Report to U.S. Forest Service, Joint Fire Science Program: The Use of High-Resolution Remotely Sensed Data in Estimating Crown Fire Behavior Variables – LIDAR Overview.  Retrieved from http://forsys.cfr.washington.edu/JFSP06/index.htm


Glennie, C., Carter, W., Shrestha, R., & Dietrich, W.  (2013, July 5).  Geodetic Imaging With Airborne LiDAR: The Earth's Surface Revealed.  Reports on Progress in Physics, 76(8).


LIDAR News Staff.  (2015, January 26).  Lower Cost Flash LIDAR.  LIDAR News.  Retrieved from http://blog.lidarnews.com/lower-cost-flash-lidar/

Marshall, P.  (2013, July 12).  The Tech That Will Make Drones Safe for Civilian Skies.  GCN.  Retrieved from https://gcn.com/articles/2013/07/12/drone-uav-sense-and-avoid-technologies-civilian-airspace.aspx

UNSY 605, Assignment 6.4, Control Station Analysis

A method of control for an unmanned ground vehicle (UGV) is a first-person view (FPV) system.  This control system allows operators to “see” from the point of view of the vehicle.  FPV control systems are useful in beyond line-of-sight (BLOS) operations, particularly in confined spaces or cluttered areas.  However, potential issues with field of view (FOV) and command, control, and communication (C3) links must be addressed with this type of control system.

            The Inspector Bots Trackbot UGV utilizes FPV in its control system.  The Trackbot is a lightweight, highly portable system (Inspector Bots, 2014).  The vehicle weighs only 10 pounds and can be transported in a single hard case.  The UGV features rubber, caterpillar-type tracks that allow the vehicle to travel over uneven terrain, obstructions, slick surfaces such as snow, inclines of up to 45 degrees, and allows it to turn 360 degrees within the space of its own footprint.  The chassis of the vehicle is also water resistant and the battery compartment provides easy access to swap batteries for continued operation.  The Trackbot’s compact design allows the UGV to enter confined spaces such as pipes, underneath vehicles, crawlspaces, and caverns.  Headlights and upgradeable infrared cameras also provide capability for low light operations (“Trackbot”, 2012).

            The control system of the Trackbot consists of a hand held control unit, transmitter, receiver, and video screen.  All control system hard/software fits into a portable hard case.  Figure 1 displays the Trackbot’s control system setup.

Figure 1.  The Trackbot’s portable control unit within its transporter case.

The video screen provides the view from the Trackbot’s on-board wide field-of-view (FOV) camera.  The Trackbot can be operated line-of-sight (LOS) using the hand held control unit.  The FPV screen is utilized for operations in which the Trackbot turns a corner in a structure or enters a confined space that prevents LOS to the operator.  The wide FOV afforded by the UGV’s camera allows the operator excellent situational awareness (“Trackbot”, 2012).

The Trackbot’s FPV system is also upgradeable to virtual reality (VR) goggle use (Inspector Bots, 2014).  The VR goggles would provide a view to the operator similar to operators of FPV racing drones.  Stock (2015) writes that FPV drone racer, Matt Denham, states that VR goggles provide an “entirely new dimension with your surroundings” and “it’s as close to being a bird as you can get”.  VR goggles would provide an immersive environment to allow a Trackbot user to operate the UGV as if he/she were the vehicle itself.  An additional improvement to the FPV system would be to utilize a motorized, gimbaled camera on the UGV.  A headset with integrated sensors would sense the orientation of the operator’s head.  Control software would link the UGV’s camera and the operator’s headset to allow the operator to look 360 degrees around the vehicle.  This improvement would provide exponentially improved situational awareness for the operator.  The immersive environment would provide benefits similar to the immersive full flight simulators used to train commercial airline pilots (AAG Staff, 2015).          

            The Trackbot’s control system utilizes a powerful transmitter and receiver to maintain C3 link between the vehicle and operator.  However, radio frequency interference can disrupt the C3 link and, potentially, control of the vehicle.  A variety of electronic equipment nearby, such as wireless/cell phones, radio towers, wi-fi routers, and power lines, can interfere with the C3 link (Derene, 2011).  This could be a particular problem with operating a Trackbot in an urban environment.  Proper bandwidth management and transmitter/receiver power would be needed to maintain the integrity of the link.  The improvement of a gimbaled camera on the UGV and linked operator headset would also require a robust C3 link and sufficient bandwidth.  These concerns would be critical to ensuring the view provided to the operator is seamless and smooth to prevent disorienting and motion-sickness inducing jerkiness.

References:
  
Alpha Aviation Group Staff.  (2015, October 30).  How AAG’s Level D Airbus A320 Full Flight Simulator Delivers Top Quality Training.  Alpha Aviation Group News and Updates.  Retrieved from http://aag.aero/how-aags-level-d-airbus-a320-full-flight-simulator-delivers-top-quality-training/

Derene, G.  (2014, March 10).  How to Fight RF Interference with Your Gadgets.  PopularMechanics.  Retrieved from http://www.popularmechanics.com/technology/gadgets/how-to/a11792/how-to-fight-rf-interference-with-your-gadgets/

Inspector Bots.  (2014).  The Trackbot [Fact Sheet].  Retrieved from http://www.inspectorbots.com/Trackbot.html

Stock, D.  (2015, August 16).  The New, Underground Sport of First-Person Drone Racing.  ArsTechnica.  Retrieved from http://arstechnica.com/gadgets/2015/08/the-new-underground-sport-of-first-person-drone-racing/

Trackbot Tracked Robot Robotic Platform [Video File].  Retrieved from

https://www.youtube.com/watch?v=7ZP90aOvJ5w 

UNSY 605, Assignment 3.5, UAS Sensor Placement

The placement of sensors on an unmanned aerial system (UAS) is an extremely important design aspect of the system.  The location of a camera in relation to the airframe will affect the field of view (FOV) of the sensor.  The placement of the camera will also determine additional equipment requirements to adjust the FOV, if necessary, during the platform’s mission.  Depending on the placement and types of the aircraft’s engines and the design of the UAS’ airframe, the camera may also require buffer equipment to ensure vibrations during the platform’s operation does not interfere with the imagery collected by the camera.  These factors will be significant considerations in the types of missions suitable for the UAS.

The DJI Inspire-1 Model T600 quadcopter would be a suitable platform to conduct aerial photography services.  The Inspire-1 can climb to over 14,000 feet but features a software limiter to keep the aircraft below 400 feet to comply with current Federal Aviation Administration (FAA) regulations (FAA, 2015).  The UAS weighs only 6.5 pounds and measures only 17.25 inches by 17.75 inches by 12 inches in size.  The quadcopter can reach speeds of 50 mph and has an endurance of approximately 18 minutes of continuous flight.  The Inspire-1 can also withstand winds up to 22 mph.  The imagery sensor mounted on the UAS is a 12.4 megapixel camera featuring a 94 degree FOV and capable of still image capture and video recording.  The camera is mounted on a stabilized gimbal to ensure maximum range of view and stability of image.  The gimbal enables the camera to pitch from -90 degrees to +30 degrees and can pan +/- 320 degrees.  The imagery system supports common jpeg, dng, mp4, and mov image and video formats.  Micro SD data cards of up to 64 GB are also supported.  The Inspire-1 also features a control mode that allows one operator to fly the aircraft and another operator to control the camera system.  The unique design of the Inspire-1 features engines mounted on hinged arms that swing up and down.  The arms pivot to the down position with the landing legs resting on the ground while the quadcopter prepares for take-off and for landing.  Once airborne, the arms pivot up to provide the camera mounted underneath the fuselage an unobstructed view (DJI, 2015).  The video below demonstrates the ease and utility of Inspire-1 operations.

Click to play video 

Figure 1.  The DJI Inspire-1 is reviewed and test flown by “Mythbusters” co-host, Adam Savage.

 The Blade FPV Nano QX quadcopter is a suitable choice for first person view (FPV) UAS competitive racing.  The Nano QX weighs only 0.77 ounces and features excellent maneuverability and handling characteristics.  The Spektrum ultra micro camera is mounted at the front of the quadcopter between two of the arms supporting two of the motors.  The positioning of the camera and the angle of the arms of the airframe ensure an unobstructed, wide FOV the operator.  The video below demonstrates the excellent visibility transmitted to the operator’s Fat Shark Teleporter V4 headset (Horizon Hobby, n.d.). 

Click to play video 

A wide range of platforms are available for aerial photography services and competitive FPV UAS racing.  The quality of the imagery systems and the FOV afforded by the design of the aircraft are extremely important aspects.  These characteristics will factor significantly in platform selection for the respective roles.  The DJI Inspire-1 and Nano QX UAS are well suited for their respective, intended roles.

References

DJI.  (2015).  Inspire-1 [Fact sheet].  Retrieved from http://www.dji.com/product/inspire-1

Federal Aviation Administration.  (2015).  Model Aircraft Operations.  Retrieved from https://www.faa.gov/uas/model_aircraft/

Flying the DJI Quadcopter with Adam Savage [Video file].  Retrieved from https://www.youtube.com/watch?v=nT5U9T9Uyok

Horizon Hobby.  (n.d.).  Nano QX FPV RTF with SAFE Technology [Fact sheet].  Retrieved from http://www.horizonhobby.com/nano-qx-fpv-rtf-with-safe-technology-blh7200  

UNSY 605, Assignment 2.5, Unmanned Systems Maritime Search and Rescue

     Teledyne Gavia ehf has produced the Gavia autonomous underwater vehicle (AUV) for a variety of roles to include maritime survey, salvage, defense, and search and rescue (SAR) missions.  This underwater platform provides useful capabilities for operators to conduct searches for stricken vessels, aircraft, and victims.  The Gavia was recently deployed in such a role in the December 2014 international effort to locate Indonesia AirAsia Flight 8501 (Rossi, 2015).

     A prioproceptive sensor suite specifically designed for the maritime environment that is fielded on the Gavia AUV is an inertial navigation system (INS) aided by Doppler velocity log (DVL) technology (Teledyne Gavia ehf, 2015).  An INS navigates by starting from a known position, orientation, and velocity.  Instruments track the position and orientation of the vehicle from the known starting point.  However, INS become more inaccurate over time and distance due to noise perturbing signals in instruments, such as gyroscopes, inducing drift (Woodman, 2007, p. 3-5).  A DVL uses bottom tracking algorithms to provide high rate, high precision data to supplement the INS and significantly reduce the errors caused by drift (Teledyne RDI, 2013).  An exteroceptive sensor specifically designed for the maritime environment that is fielded on the Gavia AUV is a side-scan sonar system.  This sonar system is specifically designed to use higher frequencies to produce high resolution images.  The imagery resolution is sufficient to identify details such as vessel shapes or human forms (NOAA, 2015).  This capability would be very useful in SAR operations.

     An improvement that would make the Gavia AUV more successful in SAR missions would be a higher capacity battery module.  Currently, two battery modules are used on the vehicle to provide an endurance of approximately eight hours (Teledyne Gavia ehf, 2015).  The ability to provide continuous operation during a SAR mission is extremely useful.  Ocean currents can move wreckages of vessels or aircraft far from the point at which they initially foundered or crashed.  An increased endurance time will increase the probability of the AUV to locate wreckage sooner before it can drift further and increase the difficulty of search operations.  The probability of locating living victims also decreases as time passes.  The ability to remain on station for longer periods would provide increased probability of locating victims in time for rescue and medical aid.  An improved battery module featuring increased endurance would greatly assist these efforts.

    An unmanned aerial system (UAS) could be deployed in conjunction with an AUV to aid in a SAR mission.  An aerial platform can search a large area in a relatively short period of time traveling at higher speeds and scanning from a higher vantage point.    A UAS such as the Boeing/Insitu ScanEagle has a service ceiling of 15,000 feet, cruising speed of 50 knots, and an endurance of 24 hours (Insitu, 2013).  By comparison, the Gavia AUV has an endurance of approximately 8 hours and a speed of approximately 5.5 knots.  The side-scan sonar on the AUV has a range between 6.5 to 131 feet (Teledyne Gavia ehf, 2015).  The ScanEagle would be able to search a wide area but cannot search beneath the sea surface.  The Gavia can detect minute details but cannot feasibly search a wide area due to the limitations of its speed and range of its sensors.  A UAS and AUV operating in conjunction could be applied to the example of the search and recovery efforts for Air France Flight 447.  The debris field of the aircraft was spotted on the ocean surface, leading search teams to eventually locate the wreckage on the sea floor (Associated Press Staff, 2009).  A UAS would search a wide area for clues such as a debris field.  Once located, an AUV would be deployed for a closer inspection.

     AUVs also possess some advantages over their manned counterparts.  A manned submersible must include accommodations for crewmembers and associated support equipment in its design.  These requirements increase the dimensions and weight of the vehicle and reduce the capacity for payload and fuel.  A manned submersible is also limited in endurance by the oxygen supply available for its crew.  An AUV can devote space, that otherwise would be used to accommodate crewmembers, to additional payload and fuel/power supply.  An AUV can also be designed in a smaller, compact overall size that would facilitate transportability to operating areas.  A smaller vehicle would also be more maneuverable in tighter spaces, such as underwater caverns or inside a shipwreck.  An AUV would also not be limited by oxygen supply for crewmembers.  The limitations on an unmanned vehicle’s endurance would be determined by fuel or power supply.  The equipment dedicated to supporting crewmembers on manned platforms can also cause interference with sensors such as sonar (Vexilar, 2015).  An AUV, lacking such equipment, would be less prone to be affected by such interference to its sensors. 

     The Teledyne Gravia ehf Gravia AUV is a suitable platform to conduct SAR and search and recovery missions.  The performance specifications and sensor suites of the platform provide extremely useful capabilities to search teams.  Manned platforms still have a role in SAR missions.  However, unmanned platforms provide a powerful resource to augment this important mission.

References:

Associated Press Staff.  (2009, June 2).  Debris Confirms Crash of Air France Flight 447.  NBC News.  Retrieved from http://www.nbcnews.com/id/31057560/ns/world_news-americas/t/debris-confirms-crash-air-france-flight/#.VjaOEG5cTkM

Insitu.  (2013).  ScanEagle System [Fact Sheet].  Retrieved from http://www.insitu.com/systems/scaneagle

National Oceanographic and Atmospheric Administration (NOAA).  (2015).  Side Scanning Sonar [Fact Sheet].  Retrieved from http://www.nauticalcharts.noaa.gov/hsd/SSS.html

Rossi, M.  (2015, January 6).  Teledyne Gavia AUV to Aid in Search for AirAsia Flight QZ8501

[Press Release].  Retrieved from https://teledynemarinesystems.com/news_and_events/press_release_view/teledyne-gavia-auv-to-aid-in-search-for-airasia-flight-qz8501

Teledyne Gavia ehf.  (2015).  Gavia AUV [Fact Sheet].  Retrieved from http://www.teledynegavia.com/product_dashboard/auvs

Teledyne RD Instruments.  (2013).  Workhorse Navigator Doppler Velocity Log [Fact Sheet].  Retrieved from http://www.rdinstruments.com/navigator.aspx

Vexilar Inc.  (2015).  Solving Sonar Interference [Fact Sheet].  Retrieved from http://www.vexilar.com/blog/2014/08/28/solving-sonar-interference

Woodman, O.  (2007).  An Introduction to Inertial Navigation (ISSN 1476-2986).  Retrieved from University of Cambridge Computer Laboratory website: https://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-696.pdf