Unmanned Aerial Vehicles (UAVs) perform a variety of missions. They are used by the military and law enforcement. They are used for environmental research, agriculture, and search and rescue just to name a few. This paper will focus on two small commercially available UAVs. One of them is the DJI Inspire1 Quadcopter used for aerial photography and full motion video. The other one is the Immersion RC Vortex 250 Pro drone used for First Person View (FPV) racing.

Both of this vehicles are light weight and commercially available quadcopters. However, their designs, sensor selection and placement differ depending on their specific missions.

The Inspire1 Quadcopter is designed to take 12-megapixel photos and produce 4K video. The reason I have chosen this vehicle for aerial photography and video is its versatility and its unique design. The Quadcopter design allows the UAV to “hover and stare” which is a perfect feature for image and video collection. The carbon fiber aero frame is light weight. This allows for increased battery life and longer flight times due to overall weight reduction. The smart power management system uses algorithms to estimate the remaining flight distance and time need to return to base and sends this information to the pilot. Retractable quadcopter arms with propellers on top lock in a lowered position when the UAV is on the ground, acting as landing gear. The arms retract in the up position in flight to allow for 360- degree unobstructed view for the camera to shoot videos and take pictures. The Inspire1 features auto takeoff and landing modes, allowing for easy handling with minimal operator training.

This UAV fulfills its mission of aerial video and photo production due to its high resolution camera sensor and its attachment via an incorporated 3-axis gimbal. It uses brushless servo motors that allow the camera to remain steady and to be locked on the subject regardless of the UAV maneuvering, which is important for clear photos. One radio transmitter allows the pilot to maneuver the UAV and another transmitter permits simultaneous inflight tilting of the camera to adjust the angle. A real-time picture can be presented to the pilot on a mobile phone, tablet or HDMI monitor, allowing the user to monitor the framing from the ground. This capability is provided by the use of the DJI Lightbridge system within the flight electronics, which features a range of up to 1.2 miles. The camera gimbal positioning also allows for easy interchanging of the camera if necessary.

Another sensor which comes in handy during photography missions is a GPS-based stabilization system, which allows UAV to hover in position even in crosswind conditions. The GPS also allows the UAV to automatically return “home” in case of signal loss. It works even if the operator is travelling in the car or on the boat allowing the return-to-home point to move anywhere operator proceeds.

The GPS sensor will also allow geo map reference and latitude/ latitude, time and date signatures on the aerial photos. This feature may be an important factor in some missions, such as real estate imaging, surveillance, security, and reconnaissance. The user can see where the UAV is located at any time during flight using live map, which also shows the most recent UAV route. The UAVs maximum speed is 50 mph, which is fast for such a small vehicle (Aguilar, 2014).

The high definition camera produces video and still images and features a 1/2.3" CMOS sensor with a 94-degree field of view lens. It allows for a wide view with an excellent resolution. The camera pans a full 360-degrees, which means that no matter which way the quadcopter turns, the camera can remain locked on the subject ("Inspire1," n.d.). Figure 1 displays Inspire1 UAV.

Figure 1. Inspire1 with camera sensor. Adapted from “DJI Inspire1 Quadcopter.” (n.d.). Retrieved from http://www.bhphotovideo.com/c/product/1097099-REG/dji_inspire_1.html/prm/alsVwDtl Copyright by DJI.

 

As we can see, for the mission it is designed, The Inspire1 is an excellent vehicle. The sensor positioning and stabilization allows it to take pictures and shoot video. The lightweight airframe and power conservation system give the vehicle longer on site times. The high definition camera is excellent for the mission requirements. The GPS sensor is a great addition not only for the vehicle tracking and operator’s situational awareness, but also for easy geo reference of the pictures and videos taken by the UAV.

Next UAV to be discussed is The Vortex 250 Pro Racing Quadcopter Drone by ImmersionRc. This UAV was specially designed for First Person View (FPV) racing. Its small size, strong airframe, light weight (only 415g without battery), and fast speeds due to custom race motors allowing it to compete on the racing circuit. The specially designed skid frame is strong enough to withstand rough landings. The UAVs carbon arms are deigned tough to survive a collision with opponents or objects. It also features a lost UAV alarm is case the vehicle crashes, which allows the user to easily locate the quadcopter. Figure 2 displays Vortex 250 drone.

Figure 2. Vortex 250 PFV UAV with forward looking camera placement. Adapted from “ImmersionRC Vortex 250 Pro racing drone.” (n.d.). Retrieved from http://www.quadcopters.co.uk/immersionrc-vortex-250-pro-racing-drone-2147-p.asp Copyright by ImmestionRC.

The Spironet 5.8Ghz antenna allows for a reliable connection with the pilot. The Fast F3 processor gives the vehicle the ability to be more responsive to pilot inputs and is able to have a sharp turning ratio. The flight camera is essentially the eyes of the racer. It is important that it is located on the nose of the UAV to provide the pilot with the direct view of what is in front. This sensor placement will allow the racer to avoid the obstacles and follow a precise flight path. This UAV includes a FatShark 700TVL v2 CMOS flight camera. It is securely mounted on the front of the UAV. To protect the sensor from impact it is mounted on a Carbon- fiber plate. The mount also dampens the camera vibration. The camera tilt can be adjusted to allow the pilot see the best field view. For the purpose of racing the high definition images are not as important as for the previous missions, so camera definition is not as good as the one used in Inspire1 UAV. However, the camera may be quickly swapped for a high definition one such as Go Pro Hero due to the quick release mechanism.

The UAV features a wireless video control. NexWaveRF 5.8Ghz transmitter with Raceband and can broadcast on up to 40 channels. The transmit channel can be easily changed via remote control. The system allows up to eight racer to fly together and is controlled via an on-screen display (OSD) so choosing the clearest channel is done through the flight transmitter. The Fatshark FPV Goggles allow the pilot to see the picture from the vehicle, as if he was flying in it. The BlackBox flight data storage can hold up to two megabytes of flash memory for race review ("Vortex 250," n.d.). The FPV goggles are displayed in the Figure 3.

Figure 3. First Person View goggles used with Vortex 250. Adapted from “Cutting edge FPV racing.”(n.d.). Retrieved from http://www.bladehelis.com/VortexPro. Copyright by ImmersionRC.

 

Since it is important for the pilot to see and analyze the video in real time, the Vortex UAV is equipped with the full-graphic OSD, which delivers in-flight updates of critical parameters. A real-time interface supports artificial horizons, fighter-jet style instrument panel and a display of flight information. The UAV status such as battery voltage, communication link are some of the parameters displayed to the pilot ("Cutting edge FPV," n.d.).

A strong airframe, high flight speed, and radio link reliability are important parameters to consider for a racing drone. A minimal number of sensors onboard allows for a simple, lightweight, and maneuverable vehicle.  Camera sensor placement with the forward view allows the pilot to see what is in front. Secure and protected sensor location is important to prevent damage in case of crash or collision.

As we can see, sensor placement and specific design characteristics of the UAV varies deepening on its mission requirements. It is important to take into consideration the specific tasks the vehicle is designed to perform and consider the sensor placement, datalink capacity, and airframe construction.

 

References

Aguilar, M. (2014). DJI Inspire1. Retrieved from http://gizmodo.com/dji-inspire-1-a-badass-drone-that-shoots-lovely-4k-vid-1658076017

Cutting edge FPV racing. (n.d.). Retrieved from http://www.bladehelis.com/VortexPro

DJI Inspire1 Quadcopter. (n.d.). Retrieved from http://www.bhphotovideo.com/c/product/1097099-REG/dji_inspire_1.html/prm/alsVwDtl

ImmersionRC Vortex 250 Pro racing drone. (n.d.). Retrieved from http://www.quadcopters.co.uk/immersionrc-vortex-250-pro-racing-drone-2147-p.asp

UNSY 605. Activity 2.5

Bluefin-21 AUV for Maritime Search and Rescue

Introduction

Unmanned vehicles perform a variety of tasks in every operational domain: air, space, ground, surface of the water and on the bottom of the sea. Unmanned underwater vehicles (UUVs) will be the focus of this paper. The underwater environment is a challenging domain of operation due to high pressure, strong currents, lack of light, extreme temperatures, water salinity, and other factors. These issues can affect underwater communications, navigation and play a roll in vehicle design, and sensors used on the underwater vehicles. In recent years, the use of UUVs in search and rescue operations has significantly increased. UUVs carry out such complicated and dangerous tasks as maritime patrol, mine detection, and searching for missing aircraft and vessels. This paper will focus on Bluefin-21 autonomous underwater vehicle (AUV), developed by Bluefin Robotics. This particular AUV was used in 2014 in search efforts for Malaysia Flight MH370 in the Indian Ocean. It scouted over 850 sq. km. of the ocean floor in an effort to locate  the missing aircraft (Tokkecar, 2014). The Bluefin AUV is suited for complicated search and rescue missions due to its extensive sensor payload and tit’s ability to operate down to a depth of 1500 meters at speeds of 2 to 4.5 knots. Its long endurance capability of 20 hours at sea makes it a perfect search vehicle. Bluefin-21 follows a preprogrammed “lawnmover” pattern to scan for debris on the sea floor. Figure 1 depicts the Bluefin-21 being recovered onto the vessel with the crane.

 

Figure 1. Bluefin-21 Adapted from “Bluefin-21” by Bluefin Robotics. Retrieved from http://www.bluefinrobotics.com/vehicles-batteries-and-services/bluefin-21/ Copyright by the Bluefin Robotics.

 

Bluefin-21 AUB sensors

The Bluefin-21 features an extensive sensor suit. The exteroseptive sensors are sensors which are responsible for providing information about vehicle’s environment and its position relative to other objects, and environment features. The Bluefin-21 is equipped with the variety of exteroseptive sensor which include:

- EdgeTech DW-216 sub-bottom profiler, which is ideal for identifying and characterizing layers of sediment or rock under the seafloor and other relevant features on the seabed (Kongsberg, n.d.).

-  Inertial navigation system, which is essential sensor for vehicles navigation underwater.

-  Ultra-short baseline system

- Side-scan sonar system EdgeTech 2200-M 120/410 kHz or optional EdgeTech 230/850 kHz can be also installed improving focusing capability. EdgeTech transmits a signal which creates a high-resolution 3D map of the seabed, helping identify man-made objects, such as aircraft, which often have right angle and sharp outlines.

 

-        Multi-beam echo-sounder Reson 7125 (400 kHz) sensor that can paint the picture of the ocean bottom to distinguish ocean floor relief and relevant features from above (Chand, n.d.)

The Bluefin-21 is equipped with GPS system. Due to degraded communication and navigation signal  propagation though water, the UAV have to ascend every 30 minute to acquire GPS signal and realign its position, resulting in about 50-100 m of navigational error (Autonomus Undersea Vehicles Application Center [AUVAC], n.d.). The Bluefin-21 is also equipped with a digital camera as an optical payload. Some of the optional payloads include sensors which measure chemical tracer concentrations or biological contents in the water, such as algae, oil or hydrothermal vent fluid (AUVAC, n.d.).

Proprioceptive sensors are responsible for monitoring self-maintenance and controlling internal status of the vehicle. These sensors include potentiometers for control surface positioning and pressure sensors for monitoring vehicle’s depth. Linear velocities determined with a Doppler Velocity Log (DVL). Angular rates, pitch and roll attitude is measures by IMU sensor.

Sensors which are responsible of monitoring vehicles state to maintain safe operations include: fault and leak detection sensors, drop weight acoustic tracking transponder, strobe, RDF and Iridium. All of these sensors are independently powered proving extra redundancy (Bluefin Robotics, n.d.).

The Bluefin-21 features the Mission Oriented Operating Suite (MOOS) and the Interval programming IvHelm. This system coordinates and programs autonomous behaviors of AUV, by controlling depth, speed, and heading based on the sensor data and required vehicle behavior (AUVAC, n.d.). Figure 2 depicts Buefin-21 Bluefin-12 AUV with a Buried Object Scanning Sonar (BOSS) integrated in its wings.

Figure 2. Bluefin-21 with BOSS sonar. Adapted from Adapted from “Bluefin-21” by Bluefin Robotics. Retrieved from http://www.bluefinrobotics.com/vehicles-batteries-and-services/bluefin-21/ Copyright by the Bluefin Robotics.

 

What one modification would you make to the existing system to make it more successful in maritime search and rescue operations?

Current design and sensor suit of Bluefin-21 AUV allows it to be a perfectly suited for search and rescue operations. However, there is always a room for improvement. Since time is a critical factor in the search and rescue missions, modification of the vehicles propulsion system to allow for faster area scanning would be beneficial. Another addition may be installation of flashlight to allow take images in the areas where natural light is restricted. Modifying the AUV launch system to allow it to be delivered using manned helicopters or unmanned hover vehicles instead of slow-moving ships may be helpful in time critical missions.

Since underwater communications and navigation is restricted due to physical characteristics of the water and signal propagation, addition of the gateway buoy would be beneficial. The gateway buoy, similar to one developed by Kongsberg and used for Remus AUVs can be used in remote AUV tracking, communication, and navigation. Gateway buoys uses standard alkaline battery and saves power by automatically going into “sleep” mode during stages of inactivity. Triangulation techniques can be used to aid in AUV location using multiple buoys deployed in the known positions. Buoys may also be equipped with GPS receiver and Iridum Satellite Modem (Kongsberg, n.d.)

 

How can the maritime system be used in conjunction with UAS to enhance its effectiveness?

Collaboration between different types of unmanned vehicles in search and rescue operations can have positive effect on the overall success of the mission. Use of the unmanned aerial vehicle (UAV) in conjunction with Bluefin-21 AUV could be beneficial. For example, the UAV payload such as cameras and infrared radars may help locate and identify debris from the a crashed aircraft or vessel and help focus the search on a particular region of interest. The UAV can also provide a relay link for AUV communications with the control station based on the ship or shore. The UAV also may deliver the UUV to the search site much faster than the sea vessel, shortening the time for delivery and launch and allowing the UUV to begin the search efforts faster in a time critical situations. For example, it is important to detect emergency locator transmitter signals and black box pinger signals in timely manner due to its limited battery life.

 

What advantages do unmanned maritime systems have over their manned counterparts? What sensor suites are more effective on unmanned systems?

UUVs can carry out dangerous, dull, and dirty tasks in the unforgiving environment of the ocean. By using the UUVs instead of manned submarines, physical risk to the crew is removed. The ability of UUV to stay underwater for extended periods of time without necessity for decompression is another advantage of UUVs. Small size of UUV is also an advantage, since it can go into confined spaces, inaccessible for large manned submarines.

One example of a sensor suite that would be more effective on a UUV is the mine countermeasure sensors. This kind of dangerous mission is a perfect task for an unmanned vehicle. For example, Bluefin12 Buried Mine Identification (BMI) System can be used in search of buried mines. This system consists of the bottom looking sonar, a Real-time Tracking Gradiometer (RTG), and an Electro-Optic Imager (EOI) (Sulzberg, Bono, Manley, & Clem, n.d.).

Sea trials of mine countermeasures using the Bluefin-21 were conducted in 2008. The mission provided important data that proved that successful sensor fusion aboard an UUV was possible. Researches used the RTG and the EOI sensors in sea trials of the Bluefin-12 to evaluate, optimize, and demonstrate its mine detection capability.

UUVs have many applications in a variety of missions and has proven that unmanned systems can successful perform challenging tasks in the dangerous and unforgiving underwater environments. This is accomplished with no risk to the human operator, UUVs can perform successful long endurance, deep ocean missions ranging from search and rescue, mine countermeasures, environmental research and patrol and reconnaissance. 

References

Autonomous Undersea Vehicles Application Center. (n.d.). MIT LAMSS Bluefin 21 configuration. Retrieved from http://auvac.org/configurations/view/187

Bluefin Robotics. (n.d.). Bluefin-21. Retrieved from http://www.bluefinrobotics.com/vehicles-batteries-and-services/bluefin-21/

Chand, N. (n.d.). Unmanned/ Autonomous Underwater Vehicles. Retrieved from http://www.spsnavalforces.com/story.asp?mid=37&id=6

Kongsberg. (n.d.). AUV gateway buoy. Retrieved from http://www.km.kongsberg.com/ks/web/nokbg0240.nsf/AllWeb/7F3D0D6DAC990552C12574B1002E8091?OpenDocument

Kongsberg. (n.d.). Sub-bottom profilers. Retrieved from http://www.km.kongsberg.com/ks/web/nokbg0240.nsf/AllWeb/1AE8CC56C6F31E51C1256EA8002D3F2C?OpenDocument

Sulzberg, G., Bono, J., Manley, J. R., & Clem, T. (n.d.). Hunting sea mines with UUV-based magnetic and electro-optic sensors. Retrieved from www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA527389

Tokkecar, P. R. (2014). Placement and motion planning algorithms for robotic sensing systems (Doctoral dissertation, University of Minnesota). Retrieved from http://tokekar.com/thesis/tokekar_dissertation.pdf

In this post I reviewed the article “Autonomous landing of an UAV with a ground-based actuated infrared stereo vision system”. In this paper the authors suggest using infrared cameras to aid in UAV landing. The infrared camera is chosen as the exteroceptive sensor for two main reasons: first, it can be used in day and night operations under all-weather conditions; second, it can be used in the environments, where GPS signal is restricted or unavailable due to terrain, obstacles or intentional signal jamming. Another advantage of using infrared stereo cameras according to the article is the system cost and complexity reduction.

Navigation of the UAV is defined as the process of data collection, data analysis, monitoring of the UAV vehicle status and its surrounding, with the goal of successful and safe mission completion. From this statement, we can see that information from proprioceptive (Internal status) and exteroceptive (outside, environmental) sensors combined together is important for success of the mission.

There are four core functions in a navigation system, they are Sensing, State Estimation, Perception, and Situational Awareness. With regard to these four functions, different types of sensors such as the Global Navigation Satellite System (GNSS), laser range scanners (LRFs), monocular cameras, and stereo cameras are been used. In this article, the authors focus on the infrared sensor as a stand along landing system or as an additional system used together with above mentioned sensors.

Considering that the landing phrase of UAV operations is one of the most complex and dangerous segments of flight, precise and timely sensory information is important for safely executing the landing maneuver. The authors point out that it is important to build in extra redundancy into the system, which is responsible for the landing phase. The main idea is to track the UAV during the landing phase and calculate the relative position between the UAV and its landing sight, based on the infrared vision system. The diagram of the system architecture including on-board sensor equipment, ground station and stereo camera sensor architecture is represented in Figure 1.

Figure 1. Architecture of the system.

The authors built and tested a calibrated binocular infrared landing system to estimate relative position between UAV and landing site. The stereo vision system is built on two infrared cameras, with model IRT301, which are produced by IRay Technology. The equipment architecture of the infrared vision landing system is presented in Figure 2.

Figure 2. Ground stereo vision landing system.

This experimental sensing system was tested using field trials, with a quadrotor and a fixed-wing aircraft. This landing system features large field of view buy using pan tilt unit (PTU) represented in the Figure 3.

 

Figure 3. Infrared video system with point-tilt unit.

Testing of the infrared based landing system had positive results. Some of the problems which were experienced during testing relate to low accuracy of fixed-wing UAV touch-down points. However, the use of the proposed system greatly increased situational awareness, aided in navigation, and in 3D position estimation methods.

Reference:

Kong, W., Zang, D., Wang, X., Xiang, Z., & Zhang, J. (n.d.). Autonomous landing of an UAV with a ground-based actuated infrared stereo vision system. Retrieved from https://tams.informatik.uni-hamburg.de/people/kong/publications/130322.IROS2013.pdf