One of the primary purposes of unmanned systems is to keep humans out of danger by performing dangerous, dirty, and dull tasks. Fires represent one of the greatest dangers to sailors, working onboard U. S. Navy ships. The Office of Naval Research (ONR) has developed a robotic firefighter to work alongside humans to fight fires. The Shipboard Autonomous Firefighting Robot (SAFFiR), which is pronounced as “safer”, performs firefighting tasks aboard the Navy ships, keeping the sailors safe and providing enhanced situational awareness for human firefighters. This unmanned ground vehicle (UGV) is a humanoid robot, which measures 5 feet 10 inches and weighs 143 pounds (Gaudin, 2016).

    The 2016 article by Sharon Gaudin talks about this amazing robot, which will potentially be a great benefit for the United States Navy. It is not only designed for the firefighting applications, but also is capable of performing basic maintenance tasks, such as checking for corrosion and leaks. By performing everyday maintenance and inspections, the SAFFiR could free up sailors for more advanced technical jobs onboard of the ship. Figure 1 depicts the prototype of the SAFFiR.

Figure 1. The SAFFiR humanoid firefighter trials. Adopted from “Making sailors ’SAFFiR’ - Navy unveils firefighting robot prototype at Naval Tech EXPO,” by T. White, 2015. Copyright 2015 by U.S. Navy.

This UGV is designed to be capable to perform autonomous operations, however, initial robot design keeps the operator in the loop, allowing the human controller to monitor and override any action of the UGV. The main goal for the SAFFiR is to allow this robot to seamlessly work alongside its human counterparts on the Navy ships, responding to verbal commands and gestures, such as pointing and hand signals (Eshel, 2015).

To enable natural collaboration with a human “fire boss”, the robot will be equipped with multimodal interfaces that will enable the robot to track and focus its attention on the human team leader. Researchers are planning to further simplify the robot interaction by using natural language commands (White, 2015).

It is designed to endure high temperature environments, recognize fire hazards, and extinguish fires using a broad range of fire suppression tools. Its upper body will be capable of manipulating fire suppressors and throwing propelled extinguishing agent technology grenades. The SAFFiR is battery powered, which gives the robot about 30 minutes of firefighting mission time, after which time the battery needs to be recharged (McKinney, 2012). As we can see, the power system design still needs to be improved to allow for longer mission endurance, when necessary. Figure 2 represent some of the features of the SAFFiR.

Figure 2. The Naval Research Laboratory's Shipboard Autonomous Firefighting Robot (SAFFiR) is a humanoid-type robot being designed for shipboard firefighting. Adapted from “NRL designs robot for shipboard firefighting,” by D. McKinney, 2012. Copyright 2012 by U.S. Naval Research Laboratory.

This bipedal robot can walk, balance, and navigate even on the moving ships, it can cross over obstacles, manipulate fire hoses, and install fire shielding equipment. It features a lightweight central aluminum construction, which allows for efficient transfers of loads throughout the UGV’s body. It’s six- axes force/torque sensor allows for strong feedback while walking.  The advanced joint movements are enabled by titanium springs installed in the robot’s “legs” (McKinney, 2012).

The SAFFiR is designed to “see” through dense smoke with a help of advanced sensor suit, including infrared stereo vision, gas sensor, and a rotating laser for light detection and ranging (LIDAR) (Gaudin, 2016). So far, the SAFFiR is in its testing stage. The first trials will take place onboard a decommissioned U.S. Navy vessel, the USS Shadwell, docked in Mobile Bay, Alabama.

The researchers are working to constantly improve and enhance the SAFFiR. The latest development for the humanoid includes a motion-planning algorithms to allow the robot to skillfully perform a variety of autonomous tasks. The U.S. Navy awarded a $600,000 grant to the Worcester Polytechnic Institute for development of the advanced motion algorithms for this UGV to work in complicated scenarios. These algorithms will allow the robot to be able to move quickly in confined spaces when working onboard a ship or submarine. It must also be able to stay balanced while the ship is moving in rough seas. Researchers are planning to improve the SAFFiR with enhanced computing power, and increase its ability to solve complicated tasks, and better communication capabilities, and longer endurance.

The main goal for the development of the firefighting robot is to prevent tragedies like the one onboard the USS Miami in May of 2012. The nuclear submarine was damaged by an onboard fire, started by a shipyard worker, while in a dry dock at the Portsmouth Naval Shipyard in Kittery, Maine. Seven people were injured during fire. Because of the degree of the damage to the vessel, the Navy inactivated the ship. (Gaudin, 2016).

Although, humanoid-type robots may seem less stable than their wheeled counterparts, the SAFFiR is showing promising results for life-saving applications, while skillfully balancing on a moving ships with the help of its advanced motion algorithms and with the constant advancements in robotic technology, humanoid-type UGVs will eventually play an important part in our everyday lives.

References:

Eshel, T. (2015). Navy scientists experiment with firefighting robots. Retrieved from http://defense-update.com/20150205_saffir.html

Gaudin, S. (2016, February 9). Navy calls on researchers to create firefighting humanoid robot. Computerworld. Retrieved from http://www.computerworld.com/article/3031657/robotics/navy-calls-on-researchers-to-create-firefighting-humanoid-robot.html

McKinney, D. (2012). NRL designs robot for shipboard firefighting. Retrieved from http://www.nrl.navy.mil/media/news-releases/2012/nrl-designs-robot-for-shipboard-firefighting

White, T. (2015). Making sailors ’SAFFiR’ - Navy unveils firefighting robot prototype at Naval Tech EXPO. Retrieved from http://www.navy.mil/submit/display.asp?story_id=85459

Sense and avoid sensor selection

Unmanned aerial systems (UAS) integration into National Aerospace System (NAS) dictate establishing regulatory standards and equipment requirements to ensure UAS operational safety. Sense and avoid technology is one of the important issues pertaining to safety of UAS. Pilots of manned aircraft are responsible to see and avoid other traffic by relying on visual detection, air traffic control radar separation, and other available sensors installed on the aircraft. Unmanned aircraft pilots often have to rely on the UAS camera sensor picture with limited field of view, which is not sufficient for the sense-and avoid requirements for operation in the NAS. That’s why proper selection, testing, and certification of sense-and -avoid technology for UAS is important.

Electro optical/ infrared (EO/IR) sensor is a sense-avoid technology selected for this paper. EO/IR is a non-cooperative sensor, which means it does not rely on the technology carried by the intruder aircraft. EO/IR is a passive sensor. Due to this sensor’s size, weight and power (SWAP) considerations, it is suitable for use in the smaller size UAS (less than 55 pounds). It is capable to operate during day and night in all weather conditions. However, current EO/IR technology for SAA may have an increased rate of false alarms generated due to clutter in images and weather conditions such as fog or clouds.

EO and IR technologies are combined in a single compact sensor create a complete SAA system. The EO sensor takes images in the visible light spectrum with a charged coupled device camera. The infrared sensor works within infrared spectrum, creating images based on temperature differentiation.

EO/IR sensors have good performance in terms of detection of azimuth, elevation and traffic coverage. However, the drawbacks of this technology is that it is restricted range and has a limited field of view (FOV). It is important to mention, that a tradeoff exists between the FOV and detection range. For example, if the EO/IR sensor has a large FOV versus a small FOV to passively scan, the distance at which it can detect an object will decrease (Pearson, Moore, Ogdoc, & Choi, n.d). The particular EO/IR sensor which is suitable for smaller size UAS was developed by HoodTech Vision. Alticam AC-10 EO/IR sensor has small size and weighs only 5,700 grams and measures 25.4 cm in diameter. It is designed for both day and night and all weather operations. The sensor also features a laser pointer, a laser range finder, and a pan-over tilt. Gimbal that tilts 45 degrees up and 90 degrees down with 360 digress endless pan capability. Since power consumption is an important parameter to consider for small UAS, the AC- 10 was designed to use half the power of similar systems, freeing power for additional sensors and saving fuel for increased mission range. Power supply range is 24-32 VDC with 31 W continuous and 55 W peak consumption (HoodTech, n.d.).

It also has an increased FOV for better traffic detection: the IR sensor has a horizontal FOV of 1.7°- 22° and EO imager features 1.1°- 31.5° FOV. Since this particular sensor is enhanced with laser pointer and range finder, its application for as a sense-and-avoid sensor is greatly improved. The laser rangefinder operates in the 30 to 3000 meter range and it is eye-safe. The slew rate of the gimbal is 60° per second.

Figure 1. Alticam AC-10 EO/IR sensor. Adapted from “Alticam AC-10 specifications,” by HoodTech. (n.d.). Copyright by HoodTech.

 The concept of operations of a laser enhanced EO/IR system for sense-and avoid is as follows:

1. The EO/IR sensor detects potential intruders.

2. The laser subsystem confirms the azimuth and elevation angles of potential traffic and estimates range of the targets.

4. The gimbal with laser sensor slews to the target bearing angle detected by the EO/IR system.

5. After this information has been analyzed and, in case the intruder traffic presence is confirmed, the bearing angles from the EO/IR and the range from the laser ranger are fused to estimate the position and velocity of the intruder. In scenarios involving multiple intruders, the gimbals/scanners may be employed to slew the laser from one intruder to another (Ganguli, Avadhanam, Yadegar, Utt, & McCalmont, 2011).

Additional specifications details of AC-10 sensor are presented in Table 1.

Sensor	Wavelength	Horizontal FOV	Pixels	Video output	Zoom
IR imager	3-5 μm	1.7°- 22°	640 x 480	NTSC	Optical 13X; digital 2X
EO imager	0.4-0.9 μm	1.1°- 31.5°	1280 x 720	NTSC	Optical 30X, Digital 0.5-2X

Table 1. EO/IR sensor specifications. Adapted from Adapted from “Alticam AC-10 specifications,” by HoodTech. (n.d.). Copyright by HoodTech.

 The EO/OR sensor with laser range founder is a suitable solution for smaller UAS sense-and-avoid requirements. It is possible that in the future most UAS will require installation of cooperative technologies for traffic sense-and avoid. Such systems as transponder based Traffic Alert and Collison Avoidance system (TCAS) or GPS-based Automatic Dependent Surveillance Broadcast (ADS-B) or other similar technology will greatly enhance the sense-and-avoid capabilities for UAS. With the rapid technological advancements and miniaturization of sensor technology, weight, size, and power requirements of many sensors are decreasing while there technological capabilities are increasing. Installation of passive non-cooperative sensor such as the one presented in this paper in combination with cooperative active sensor such as TCAS will greatly enhance UAS sense and avoid capabilities.

References

Ganguli, A., Avadhanam, S., Yadegar, J., Utt, J., & McCalmont, J. (2011). Multiple intruder tracking using a laser enhanced EO/IR sense and avoid system. Retrieved from American Institute of Aeronautics and Astronautics: http://enu.kz/repository/2011/AIAA-2011-1478.pdf

HoodTech. (n.d.). Alticam AC-10 specifications. Retrieved from http://www.hoodtechvision.com/products/detail/alticam-ac-10

Pearson, J., Moore, Z., Ogdoc, J., & Choi, F. (n.d). Design of sense-and-avoid standards for RQ-7B Shadow under loss-link. Retrieved from http://seor.gmu.edu/projects/Capstone_2013/UAS_IEEE_Final_24Apr13.pdf

 

Control station analysis: REMUS 600

This paper is based on the REMUS 600 autonomous underwater vehicle (AUV) designed by the Oceanographic Systems Laboratory of the Woods Hole Oceanographic Institution. This 12.75 inch in diameter AUV was developed for variety of underwater missions including environmental research, underwater mapping, and performing mine countermeasures operations.

The REMUS 600 features a modular design, which allows for easily reconfiguring of its sensors for different missions. The vehicles endurance is up to 70 hours at speeds of 5 knots. The REMUS 600 can operate at depths up to 600 meters. With its increased payload it has a range of 286 nautical miles (Patterson, 2009). 

The vehicle is equipped with variety of sensors, which include a Kearfott KN-4902 Inertial Navigation System (INS), and an Acoustic Doppler Current Profiler (ADCP). A tail mounted GPS antenna also provides WIFI connectivity at up a 2.5 miles range. An Iridium satellite link is used for long range communications with the vehicle, enabling the AUV to “call home” from virtually any location. The REMUS 600 also carries a micro modem supporting the Compact Control Language. This feature allows real-time transmission of acoustic vehicle parameters and data to either a laptop or the vehicle tracking device. This control feature allows the operator to follow the status of the AUV and monitor the mission progress.

Other sensors installed on the AUV include pressure sensor, side scan sonar, temperature, and conductivity probes. Optional sensors include a dual frequency side scan sonar, a video camera, an acoustic imaging sensor, a synthetic aperture sonar, an acoustic modem, and a fluorometers (Kongsberg, n.d.).

These sensors provide data on the vehicle internal status and its location as well as a variety of environmental data. Such information as water quality, salinity, fluorescence, temperature, and bathymetry. The synthetic aperture sonar produces high resolution images combined with a large swath width as compared to conventional single beam side-scans. Laser The Scaler Gradiometer (LSG)/ Re-acquisition Payload assembly combines a magnetometer with an electronic still camera and short range, dual frequency side scan sonar. It collects data from a large search area and provides classification of targets such as buried mines. The sensor data is downloaded at the end of each mission upon recovery of the AUV (Stokey & Roup, n.d.).

By joining the sensor data with the navigation data, 2D and 3D visualization of the environmental parameters can be displayed. Data presentation methods range from color coded diagrams, still images acquired by the camera, and navigation maps from sonar imagery taken by side scan sonar. The temperature sensor data can be presented via diagrams with color coded information and combined with depth sensor and navigation data to present a complete picture of the area. Figure 1 presents the data presentation methods in a form of diagram. Figures 2 and 3 present the data from the camera and side scan sonar.

Figure 1. Water temperature at various depths. Adapted from “Development of REMUS 600 AUV,” by Stokey, R., & Roup, A. (n.d.). Copyright by WHOI.

 

  

Figure 2. Data presentation methods: 5 meter altitude electronic still image, with 200 W-S strobe illumination (right) and 900 kHz, 30 meter range scale sonar image (left). Adapted from Adapted from “Development of REMUS 600 AUV,” by Stokey, R., & Roup, A. (n.d.). Copyright by WHOI.

Figure 3. SAMS II, MSN012, 300kHz Side Scan Image showing transit across fault. Adapted from Adapted from “Development of REMUS 600 AUV,” by Stokey, R., & Roup, A. (n.d.). Copyright by WHOI.

 

The control station of the REMUS AUV can be based on shore or on a support ship. The operator is interacting with the vehicle using simple laptop. The AUV control computer is based around the PC-104 technology. The CPU is assembled on a motherboard with eight 12-bit analog to digital channels, input/output ports, power supplies, and other interface circuitry. The user controls the AUV and monitors its status through its diagnostic software and communicates via an RS-232 serial link. The REMUS vehicle interface program, called REMUS VIP is designed to run on a laptop equipped with Windows. The Vehicle Interface Program (VIP) is used for control and monitoring of the AUV. The interface program allows the operator to plan the mission, perform vehicle operational maintenance checks, download and analyze sensor data. The VIP features a Windows based operational interface, a quality control check, and an easy to read vehicle parameters indicators ("REMUS," n.d.).

The vehicle diagnostic software display the status of all vehicle sensors. The operator can easily control the vehicle via sliders and buttons. The mission route can be uploaded via the VIP interface, which includes route points and the location of the transponders. As we can see from the Figure 4 the status of all major sub-systems and diagnostic messages is available to view on a single screen, which reduces the need to switch between screens and allows the operator to focus his attention on one monitor. All telemetry data is recorded by the vehicle during its mission and is available for later review. This interface design allows the operator to control the vehicle while monitoring vehicle health and sensor data at the same time (Woods Hole Oceanographic Institution [WHOI], 2007).

Figure 4. Graphical user interface is highly intuitive. Adapted from Adapted from Adapted from “Development of REMUS 600 AUV,” by Stokey, R., & Roup, A. (n.d.). Copyright by WHOI.

 Communication between the vehicle and the operator is conducted via a standard Ethernet connection. A graphic user interface is intuitive and allows the controller to view a map of the mission at any time, it includes an integrated text editor for uploading the mission parameters. The software also features an automatic error inspection performed on all aspects of the planned mission. The error check generates a warning messages in case any mission parameters are incorrect. A color coded messages of mission parameters allow for at a glance vehicle check: green color indicates normal status, and red indicates a fault.

 The REMUS AUV can also use gateway buoy for communication with the control station. It allows for remote monitoring, tracking, and control. The AUV may surface, uplink with the buoy, and send information to the operator.

 One of the challenges of REMUS control pertain to the vehicle’s operational environment. The underwater operational domain present such restrictions as control and datalink signal constraints. GPS, Iridium, and WiFi signals are unavailable when AUV is operating under water. Retrieval of the mission data is performed after the vehicle surfaces. Most of the information from the vehicle needs to be processed after retrieval. One of the suggestions for improving AUV operation is installing data processing system directly onboard of the vehicle, therefore data could be preprocessed before it is downloaded. When the AUV surfaces, the processed data can be send over limited bandwidth to the operator. It can help review the mission in real time and make decisions on how to proceed with the survey in the most efficient way. If no bandwidth is available, the preprocessed data can be quickly uploaded at the end of the mission and will require minimum processing after upload.

Another improvement that can be recommended pertain to the control station design. Most of the data from the REMUS is presented in a visual format, which is a one-sided approach. Although the computer screen presents a variety of useful sensory information for the controller, it can be overwhelming and fatiguing. Although the control station feature a simple interface based on a windows laptop, some improvements may help increase operators situational awareness. For example, incorporation of audible alarms in case of vehicle parameters are out of normal. Although most of the AUV operation is autonomous, while vehicle is on the surface it is possible to control it path by the use of a control joystick that could incorporated a haptic feedback system.

References

Hydroid REMUS 600 autonomous underwater vehicle capabilities. (n.d.). Retrieved from http://subseaworldnews.com/2013/02/12/video-hydroid-remus-600-autonomous-underwater-vehicle-capabilities/

Kongsberg. (n.d.). REMUS 600. Retrieved from http://www.km.kongsberg.com/ks/web/nokbg0397.nsf/AllWeb/1BE833604CE513AEC12574AB0044BDF3/$file/remus600web.pdf?OpenElement

Patterson, J. (2009). AUV description. Retrieved from http://www.soest.hawaii.edu/OE/kilonalu/AUV/Remus.htm

Stokey, R., & Roup, A. (n.d.). Development of REMUS 600 AUV. Retrieved from http://auvac.com/uploads/configuration_spec_sheets/Remus%20600%20Development.pdf

Woods Hole Oceanographic Institution. (2007). AUV REMUS. Retrieved from http://www.whoi.edu/sites/remus/

Draganflyer X8 data format, protocol, and storage

Data gathered by the variety of sensors installed on the unmanned aerial vehicle (UAV) is an essential component of the vehicle’s mission. The methods of data storage, processing, and dissemination can differ from one system to another. This paper focuses on the Draganflyer X8 helicopter UAV used for aerial video and photography. This UAV performs a variety of missions including wildfire control, law enforcement operations, crime scene investigations, industrial inspections, and commercial photography and videography. The Draganflyer features a quadcopter design which allows the vehicle to ”hover and stare.” The UAV has eight blushless electric motors which allow for heavier sensor payload capability and more flight stability even in the windy conditions. The Draganflyer X8 can carry up to 1.7 pound in camera equipment for photo/video and surveillance missions and can fly for up to 20 minutes on one battery charge (Draganfly, n.d.).

The UAV’s sensors suit includes camera equipment and a total of eleven sensors which are responsible for vehicle position and control. The standard camera sensor is a Sony NEX5R with an optional thermal FLIR (Forward Looking Infra-Red) attachment. The camera features a remote tilt, shutter, and a wireless video feed (FLIR Tau 320 9Hz). The video recorder also has onboard data storage. As an option, the Draganflyer can be equipped with a remotely operated 10MP still camera and a 1080p video camera ("Draganflyer X8," n.d.). Figure 1 depicts the Draganflyer X8 and points out some of its key features.

Figure 1. Draganflyer X8 and its sensors and features. Adapted from “Draganflyer X8 tech specs,” by Draganfly, n.d. Retrieved from http://www.draganfly.com/uav-helicopter/draganflyer-x8/specifications/ Copyright by Draganflyer.

An additional upgraded camera sensor for the Draganflyer X8 is the new IP video camera. The IP video cameras distribute digital video via an 802.11n 5.8GHz Wi-Fi connection. The advantage of digital video is that it is less susceptible to random noise than standard analog video. The captured picture is changed to zeros and ones which in turn are transferred as high and low power radio signals. The receiver changes these low and high power signals back to zeros and ones where a computer reconstructs it back into a video. This digital data transmission method eliminates the negative effects of signal noise. The video is transmitted over a dedicated wireless network and is encrypted for additional security. This also safeguards the data from unauthorized viewing ("Digital and raw data," n.d.). The digital video can be stored in the internal memory before transmitting it to the ground station. Also a real-time video stream can be transmitted over the internet to the end user.

The data format produced by the Draganfly varies depending on its mission. For commercial photo missions the digital camera records images in the most common formats such as JPG, BMP, and TIFF. Basically, when a picture is transferred from a camera, it’s coded as different lighting and color shades for each pixel on the camera’s charge coupled device (CCD) device. The CCD chip consists of an array of light sensitive pixels. Each pixel generates an electric current when a photon strikes it, this is known as the photoelectric effect. This current is read from each pixel and then recorded in memory as a series of light levels and colors as a raw image. After that raw format is converted into JPG, TIFF, or BMP format.

However, for law enforcement applications the raw file format is the best form of data used as evidence. By using the raw file format in the investigation law enforcement personnel are less likely to miss any detail, which may be lost during image processing.

The ground control station (GCS) connects to the UAV via a 2.4GHz control, sensor, and adjustment link with the Dragan Eye Pro 5.8GHz wireless video receiver. The video feed from the vehicle can be viewed in real time either on the monitor or using video glasses. The handheld GCS is optional, but it features an innovative design by combining the handheld controller and the video terminal in one compact station. It runs on a Linux operating system on an Intel Atom processor. The operator can fly the vehicle, view the video feed form the camera, and monitor UAV status on the same display.  Figure 2 represents split view screen for video monitoring and the flight parameters display.

Figure 2. Flight parameters and video screen. Adapted from “Draganflyer X8 tech specs,” by Draganfly, n.d. Retrieved from http://www.draganfly.com/uav-helicopter/draganflyer-x8/specifications/ Copyright by Draganflyer.

 

Several sensors are installed on the X8, which support the vehicle’s navigation, control, and autonomy levels. These sensors include: 3 gyros, 3 magnetometers, 3 accelerometers, an inertial measurement unit (IMU), a barometric pressure sensor, and a GPS receiver. The pilot can choose the vehicle’s degree of autonomy, which include altitude hold, position hold or manual throttle. The operator can select manual throttle mode during which he can control vehicle’s altitude by use of thrust and the UAV will automatically holds the selected heading and maintain level flight using the IMU and magnetometer. A preset altitude can be also automatically controlled using the pressure sensor. Automatic position hold is accomplished by using a combination of the pressure sensor and the GPS (Nahon, Sharf, Harmat, & Khan, n.d.).

The GPS sensor is a nice addition to the sensor suit of the UAV. The GPS is used for vehicle tracking, navigation, and position hold. The GPS has a backup power supply Lithium polymer battery, providing redundancy in case the main power source is depleted. It also ensures that vehicle location and speed data will be accessible to the operator even in case of main power failure. The GPS position update rate is 4Hz. All the GPS data is being uploaded to the “black box” recorder on the Draganflyer.

The “black box” flight recorder feature becomes handy for post flight study, crash log reviews, or malfunctions troubleshooting. The “black box” consists of removable 2GB MicroSD memory card installed onboard of the UAV. It loges data from onboard sensors and records such parameters as datalink quality, speed, orientation, altitude, and heading.

Power to the vehicle’s motors and sensors is supplied by the rechargeable 14.8V Lithium Polymer battery with 5400mAh capacity ("The Draganfly technical reference manual," n.d.). Voltage requirements for the camera sensor is 8 Volts to 32 Volts and power consumption is less than 2 Watts. The Dragan Eye 5.8GHz Wireless Video Transmitter is regulated at 5V DC and capable of sourcing 0.8A (RCtoys, n.d.). Barometric pressure sensor and airspeed sensor’s power requirements are between 3V and 16V. For the accelerometers, power requirements range between 4V to 16V for low G sensor, and between 4 to 6 V for high G sensor ("Draganfly technical reference manual," n.d.).

The Draganflyer X8 features a low battery power warning system, which monitors the battery voltage and transmits voltage information to the operator control station. Both audible and visual warnings will alert pilot of a low power situation. This alert allow enough time for the operator to land the vehicle safely. The GPS position will be recorded for vehicle retrieval.

The UAV uses two different frequency bands. One for its video sensor data downlink and separate one for the control signals. This technique reduces interference between the two frequency bands. The control signal is broadcasted at 2.4GHz and the video signal is transmitted at 5.8GHz.

The author recommends a possible improvement for the UAV’s data handling and treatment. It is possible to use the cloud architecture for data processing and distribution. By downloading real-time video and photo data to cloud, multiple users can have access to it simultaneously. It would be especially beneficial for law enforcement, crowd control, reconnaissance, search and rescue, and wildfire control. The Cloud architecture would provide secure data storage, and easy fast access to the necessary data for the end user. The Cloud architecture would also be useful if several UAVs were used to perform a certain mission at the same time. For example, if a formation of the UAVs were used to survey the large area, uploading the video data to the cloud would allow the user to view the “bigger picture” in real time with fast access.

References

Digital file & RAW formats usage in UAV aerial photo acquisition. (n.d.). Retrieved from http://www.draganfly.com/news/2009/06/16/digital-file-raw-formats-usage-in-uav-aerial-photo-aquisition/

Draganfly. (n.d.). Draganflyer X8 tech specs. Retrieved from http://www.draganfly.com/uav-helicopter/draganflyer-x8/specifications/

Draganfly technical reference manual. (n.d.). Retrieved from http://www.cs.unc.edu/Research/stc/FAQs/Cameras_Lenses/PtGrey/DragonflyTechnicalReference.pdf

Draganflyer X8 8-Rotor UAV Helicopter Provides High definition wireless video and high resolution photographs. (n.d.). Retrieved from http://www.cameratown.com/news/news.cfm?id=9559

Nahon, I., Sharf, N., Harmat, A., & Khan, W. (n.d.). Ground Effect Experiments and Model Validation with Draganflyer X8 rotorcraft. Retrieved from http://mattmichini.com/pubs/ICUAS_2014.pdf

RCtoys. (n.d.). Manuals and technical data sheets. Retrieved from http://www.rctoys.com/pdf/Dragan%20Eye%2058TX%20Manual.pdf

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