Adaptive Cruise Control

The past decade has seen a rapid development of advanced driver assistance systems (ADAS). Through the development of intelligent systems based on detection onboard detection and perception, engineers aim to significantly improve road safety. When these systems are fully developed, advanced driver assistance systems (ADAS) can detect potential unsafe conditions early and avoid the possibility of a crash. One of the big advanced driver assistance systems (ADAS) applications currently in use is the Adaptive Cruise Control system (ACC) (Padhi, 2019).

The Adaptive Cruise Control system is usually detected through the Radar and Lidar sensor suite that is installed in front of the vehicle. The radar sensors help the Adaptive Cruise Control maintain the speed that the driver sets as long as the road in front are free of any vehicle or obstacles and then gently slows down by engaging the brake system when the vehicle detects slowing vehicles at a predetermined range (Bosch, 2018).

One challenge facing the Adaptive cruise control is that it works well when a car directly follows another car but often fails to detect stationary objects. Adaptive cruise control is programmed to focus on maintaining a safe distance from other moving vehicles and to ignore stationary objects as the human operator should be able to steer clear of stationary objects. The result is not always the case. This situation is most likely going to result in a crash. The software to complement and utilize the full potential of autonomous-vehicle hardware still has a way to go. Development timelines have stalled given the complexity and research-oriented nature of the problems (Padhi, 2019).

The ability to detect both moving and stationary vehicles and objects will be the major update to the Adaptive Cruise Control. The field of advanced driver assistance systems still has a long way to go due to the complexity of developing the necessary software technology.

References

Bosch. (2018). Adaptive cruise control. Retrieved from https://www.bosch-mobility-solutions.com/en/products-and-services/passenger-cars-and-light-commercial-vehicles/driver-assistance-systems/adaptive-cruise-control/

Padhi, A. (2019). Autonomous-driving disruption: Technology, use cases, and opportunities | McKinsey. Retrieved from https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/autonomous-driving-disruption-technology-use-cases-and-opportunities

FIRRE UGV Joint Battlespace Command and Control System

The Joint Battlespace Command and Control System (JBC2S) is the command-and-control element for the Family of Integrated Rapid Response Equipment (FIRRE) such as the FIRRE UGV. JBC2S is a network-centric, geospatial command and control system that allows the field commander and above to plan and execute missions utilizing multiple and disparate manned and unmanned assets. It utilizes standard map formats (GeoTIFF, DNC, CADRG) for displaying map data and for tracking asset placement and movement.

JBC2S is a fusion of the framework of the Multiple-robot Operator Control Unit (MOCU), the functionality of the Multiple Resource Host Architecture (MRHA). The look of JBC2S is much more improved over the MRHA through the display of raster graphics data in addition to vector graphics data. The use of raster images reveals much more detail about the environment and presents a modern, state-of-the-art user interface (Kramer et al., 2006). JBC2S control station operates either in Monitor mode, in which the operator observes and monitors the status of the unmanned vehicles and sensors or the operator is in direct control of a single resource.

The FIRRE UGV provides telemetry data such as engine speed, engine temperature, hydraulic pressure, hydraulic temperature, track speed, fuel level, battery voltage, and obstacle detection data to the JBC2S through the MRHA IDD protocol. It also provides the pan/tilt positions of a SeaFLIR imager and the AN/PPS-5D radar located on the FIRRE UGV. JBC2S uses pan/tilt information to display coverage areas for these sensors on the map. The Platform Get Status response includes several flags such as GPS failure, emergency halt, low-battery warning, tamper alarm, and diagnostic failure. (Kramer et al., 2006).

The look and feel of the JBC2S is much better with the incorporation of the ArcGIS Engine architecture which is a library of embeddable GIS components such as the toolbar, ArcMap (2-D), ArcGlobe (3-D), and ArcScene (3-D) components.

Reference

Kramer, T. A., Laird, R. T., Dinh, M., Barngrover, C. M., Cruickshanks, J. R., & Gilbreath, G. A. (2006).  FIRRE joint battlespace command and control system for manned and unmanned assets (JBC2S). Paper presented at the , 6230 623020. doi:10.1117/12.666191 Retrieved from https://www.spiedigitallibrary.org/conference-proceedings-of-spie/6230/623020/FIRRE-joint-battlespace-command-and-control-system-for-manned-and/10.1117/12.666191.short

UAV Data Storage

In most cases, UAV flight time such as the DJI Phantom 4 Pro will fly between 5 minutes to a maximum of about 30 minutes maximum. For UAVs with the capability to take pictures and record videos, pilots can quickly realize that in about to minutes, their UAV camera’s SD card storage is quickly filling up. UAVs such as the DJI Phantom 4 Pro can allow a maximum of 128 GB of SD. Taking pictures and recording high-quality 4K videos can see one’s storage fill up very fast. 128GB model will allow owners to record up to about 6 hours of 4K video. many technologies are available to enable UAV operators to continue to fly and shoot video and take pictures on their UAV camera without completely running out of onboard camera storage.

One way to decrease the size of data produced from sensors is the use of codecs. A codec is a software that compresses videos to a manageable data size than the original file. One of the most popular type of codecs is H.264 Codec. An H.264 codec software enables the recording of HD digital video at very low data rates. The H.264 compresses video to about half the space required to save a standard digital video (MPEG-2) (DivX, 2019). Phantom 4 Pro allows for record UHD 4K (4096X2160) at 60fps, at a maximum bitrate of 100Mbps using the H.264 codec (DJI, 2019).

Another method of freeing up storage space is to directly upload images and videos on cloud storage. A good example is the Memery’s Dragonfly app that allows the operator to edit recent images and videos and then transfer the edited footage to cloud storage. The drawback to the Dragonfly app is the price. There are a lot of reasonably priced cloud storage alternatives such as Google One and Dropbox cloud storage services

References

DIVX. (2019, ). H.264 definition. Retrieved from https://www.divx.com/en/software/technologies/h264/

DJI. (2019). DJI Phantom 4 pro – specs, tutorials & guides – DJI. Retrieved from https://www.dji.com/phantom-4-pro/info

Sensors used in UAVs

Sensors used in UAVs are mostly categorized into Navigation Sensors and Sensors used for missions. Most of the sensors used for navigations on UAVs comprise of sensors such as Global Navigation Satellite Systems (GNSS) which includes the Global Positioning Systems and the Inertial Navigation System. GPS and INS complement each to the point that they are the preferred sensors for the majority of autopilot systems (Mejias, Lai, & Bruggemann 2015)

Other sensors used for navigations or surveillance include the Electro-Optical (EO) Sensors and Radio- Wave Sensors

Electro Optical (EO) Sensors;

i.                    Visible Spectrum: These are either digital still cameras or machine vision webcams that are used to take pictures or provide a continuous stream of images respectively. This type of sensor cameras is mostly used in aerial photography.

ii.                  Infrared sensors:  Infrared cameras that are sensitive to light at a long wavelength and form images using infrared radiation in the spectrum at wavelengths of 14,000nm.

iii.                Hyperspectral Imaging:  these are sensors that acquire image data simultaneously in multiple adjacent spectral bands. This type of sensor is mostly used for identifying different compositions of materials

Radio- Wave Sensors

Airborne Radio Detection and Ranging (Radar) and Light Detection and Ranging (Lidar) systems are used to determine the range, altitude, direction and speed of objects by measuring signal return time of transmitted controlled radio pulses. Radar sensors such as the Ground Proximity Warning Systems (GPWS) have been widely used in the aviation world. Radars are also recently being used in the automotive industry for collision warning systems. ( Mejias, Lai, & Bruggemann 2015)

Exteroceptors (External) and Proprioceptors(Internal)

Exteroceptors are sensors that allow the robot of unmanned systems to perceive or interact with its environment whole Proprioceptors sensors measure the internal kinematic and dynamic parameters of the unmanned system. Such parameters include the amount of torque exerted by the actuator. Exteroceptors are grouped into contact and non-contact sensors. The contact sensors perceive their environment by touching the objects and shaped in its environment while non-contact sensors obtain information about its environments without physical contact. Such non-contact sensors include pneumatic sensors, ultrasonic sensors, and optical sensors (Gupta, Arora, & Wescott, 2016)

Sensor Review
 https://ieeexplore-ieee-org.ezproxy.libproxy.db.erau.edu/xpls/icp.jsp?arnumber=4772754

For the sensor review, I have selected the journal article that uses the Miniature Strapdown Inertial Navigation System (mini INS) with inertial microelectromechanical systems (MEMS) for control of different UAVs in the autopilot mode. Inertial Navigation System sensors as noted earlier are used for navigation. The Miniature Strapdown Inertial Navigation System (mini INS suit this mission as it is low cost with small overall dimensions and consumes very low power. The sensor can provide the required accuracy of determining the attitude, position, and velocity of the UAV. The use of the inertial system as the main component of the autopilot provides the required flying accuracy with the capability of UAV destination to the desired waypoint at a given time and tracking the predefined path. (Kortunov, Dybska, Proskura, & Kravchuk, 2009)

The disadvantage of using this system in an autonomous mode is hampered since the instability of MEMS sensor characteristics causes fast accumulation of errors in the determination of navigation data. The effective approach to solving this problem is the integration of mini INS with different external measuring devices like GPS navigation, which is considered as the most precise facilities of determination of moving object position, magnetic compass, and air data sensor (Kortunov, Dybska, Proskura, & Kravchuk, 2009)

References

Gupta, A. K., Arora, S. K., & Wescott, J. R. (2016). Industrial automation and robotics: An introduction., 390-401. Retrieved from https://ebookcentral-proquest-com.ezproxy.libproxy.db.erau.edu/lib/erau/reader.action?docID=4895078&query=industrial+automation+and+robotics%C2%A0(Links%20to%20an%20external%20site.)#

Kortunov, V. I., Dybska, I. Y., Proskura, G. A., & Kravchuk, A. S. (2009). Integrated mini INS based on MEMS sensors for UAV control. Retrieved from https://ieeexplore-ieee-org.ezproxy.libproxy.db.erau.edu/xpls/icp.jsp?arnumber=4772754

Mejias, L., Lai, J., & Bruggemann, T. (2015). Sensors for missions Springer, Dordrecht. Retrieved from https://search.credoreference.com/content/entry/sprunmanned/sensors_for_missions/0

Reusable Rocket Launchers

The U.S. military began experimenting with unmanned aircraft as early as World War I. By World War II, the unmanned craft could be controlled by radio signals, usually from another aircraft. Vehicles that could return from a mission and be recovered appeared in the late 1950s. Today, Unmanned Aerial Vehicles (UAVs) perform a wide range of missions and are used by all four branches of the military.  UAVs are used to satisfy requirements for military and commercial markets to include reconnaissance, surveying, wildlife management, Space missions, border control, commercial delivery, and many more missions.

Progress in recent technologies has enabled space drones to be considered as valuable platforms for planetary exploration. Thus, drones and especially Unmanned Aerial Vehicles (UAVs) have had extremely high progress to be applied for planetary science missions.  (Hassanalian, Rice, & Abdelkefi, 2018). There is also the chance of using UAVs and rockets for tourism to Mars. However, whether the mission is for tourism or research, space exploration is very expensive. One of the most expensive parts of launching a UAV into space is the launch vehicle. Most of the launch cost comes from building the rocket, which flies only once. Compare that to a commercial airliner – each new plane costs about the same as Falcon 9, but can fly multiple times per day, and conduct tens of thousands of flights over its lifetime. Following the commercial model, a rapidly reusable space launch vehicle could reduce the cost of traveling to space by a hundredfold. (Post, 2015).

SpaceX has the designed the Falcon 9 rocket and the reusable launcher called the Grasshopper, a 10-story Vertical Takeoff Vertical Landing (VTVL) booster/launcher. While most rockets are designed to burn up on reentry, SpaceX rockets are designed not only to withstand reentry but also to return to the launch pad for a vertical landing.   The Grasshopper VTVL vehicle represents a critical step towards this goal. To date, a fully reusable vehicle has not been successfully developed.  As such, the Grasshopper testing program is incredibly challenging.  Below are videos of our most recent test in which Grasshopper rose 24 stores--or over 260 feet--hovered for approximately 34 seconds and landed safely back on the centermost part of the pad.  Spacex ’s rapidly reusable space launch vehicle could reduce the cost of reaching Earth orbit by a hundredfold(Shanklin, 2013).


SpaceX demonstrated the effectiveness of the reusable launcher by successfully launching an Unmanned Falcon 9 rocket into space. the Falcon 9’s Crewed Dragon capsule separated from the first stage booster which came back to Earth, using its engines to slow for a touchdown on SpaceX’s drone ship in the Atlantic Ocean, ready for inspections and refurbishment before another mission This success has opened a new front in space exploration. The launch of the unmanned crewed rocket opens an opportunity for spaceX and Elon Musk to achieve the aim of sending humans to space on space tourism and setting up a space station on Mars. The US military is looking to incorporate this system of launch into its fleet of space UAVs after full testing.

References

Hassanalian, M., Rice, D., & Abdelkefi, A. (2018). Evolution of space drones for planetary exploration: A review. Progress in Aerospace Sciences, 97, 61-105. doi:10.1016/j.paerosci.2018.01.003

Post, H. (2015). Reusability: The key to making human life multi-planetary. Retrieved from https://www.spacex.com/news/2013/03/31/reusability-key-making-human-life-multi-planetary

Shanklin, E. (2013). Reusability. Retrieved from https://www.spacex.com/reusability-key-making-human-life-multi-planetary

UAS Security Challenges

As early as 2004, NASA’s “Civil UAV Capability Assessment” listed 30 categories of private-sector organizations with a potential interest in UAV use, including those in forestry management, crop dusting, and coastal search and rescue. (Pitchford, n.d.). The number of UAS has since increased to tens of thousands since then. With this expansion comes the security challenges. The FAA has had challenges in regulating UAS use and they continue to update regulations to enable safe and efficient use of UAS.

Notably, even if FAA standards are imposed, safety might still be at risk unless security standards are mandated. The 2011 crash of a CIA drone in Iran underlines that unless a system can withstand hacking, safety remains at risk. In that incident, local authorities claimed that they had diverted the vehicle by hacking its GPS. Their claim gained credence when Professor Todd Humphreys of the University of Texas and a group of U.S. researchers hacked a UAV in front of representatives of the U.S. Department of Homeland Security. The team spoofed an onboard GPS receiver by mimicking the actual signals sent to the global positioning device to trick the UAV into following different commands.

In more recent times, people have used UAS to cause disruptions to flights and passenger travels. Tens of thousands of passengers have been disrupted by drones flying over one of the UK's busiest airports. The number of aircraft incidents involving drones has grown dramatically in the past few years. In 2013 there were zero incidents, compared to almost 100 last year(BBC, 2018).

With these security threats and disruptions, it is very important to quickly obtain UAS information such as registration number during or after incidents. Previously, owners of small unmanned aircraft were permitted to enclose its FAA-issued registration number in a compartment inside of the device, as long as the compartment could be opened without a special tool. (Ashworth, 2019). However, members of the law enforcement and security communities subsequently expressed concerns that the current rule presents an imminent risk of harm to first responders. Law enforcement and security officials advised that requiring first responders to physically handle or disassemble a drone to obtain the registration number poses an unnecessary safety and security risk to those individuals, as well as to others in the area, because of the potential for the UAS to conceal an explosive device in an enclosed compartment. (Coburn, 2019).

To mitigate the imminent security concerns to law enforcement, the FAA issued new regulations requiring unmanned aircraft systems (UAS or drones) to display their registration number on the exterior of the aircraft, effective February 25, 2019. (Coburn, 2019).

This new rule reflects the challenges and complexity of the UAS industry. Comprehensive rules and standards will continue to change as UAS reaches a wider use and more challenges emerge.

References

Ashworth, S. (2019). Show me the sticker: FAA issues new rules on drone registration labels. Retrieved from https://www.radioworld.com/news-and-business/business-and-law/show-me-the-sticker-faa-issues-new-rules-on-drone-registration-labels

BBC. (2018, December 20,). Drones ground flights at Gatwick. Retrieved from https://www.bbc.com/news/uk-england-sussex-46623754

Coburn, T. (2019). FAA announces new drone rule requiring visible UAS registration number. Retrieved from https://www.jdsupra.com/legalnews/faa-announces-new-drone-rule-requiring-89675/

Pitchford, M.(n.d.) What's needed to ensure safety and security in UAV software. Retrieved from http://mil-embedded.com/articles/whats-needed-ensure-safety-security-uav-software/

Case Analysis Effectiveness

The case analysis tool for this course was a very effective learning tool for keeping communication with peers.  This method and format of research and analysis are very structured. The case analysis tool allows the student to research the subject matter and gather as much information as possible that pertains to the overall effectiveness of the topic.

          The case analysis tool helps the student focus on the main topic or points of the project while analyzing how it will impact a society or industry. The case analysis tool takes a student’s view and idea on a subject and further expands the scope across a wider view to further test the relevance or irrelevance of an idea on the problem.

The case analysis project can help students think critically about the role of UAS in the future of UAS civilization. It made me think about the issues that will limit the applications that the system would be used for. To utilize UAS to its full potential, all issues are needed to be addressed.

The case analysis tool can be used in many business settings which offer an employee the opportunity to present a case before a team and provide their point of view on various subject matter ranging from which investments to make, capital investments, program decisions, design choices, and engineering changes.

          Finally, the case analysis tool enables peer review work done, this is very helpful as it ensures that ideas are being exchanged between student peers and in a real project setting, communication about a project is in a good flow. The layout of the tool also aids the student by offering the possibility of expanding the development of their research design. The recommendations provided by both the tutor and peers helps the student gain a much deeper appreciation and understand of the research and analysis process, which is the main key or benefit from utilizing the case analysis tool in a student’s research project. The initial peer review of the abstract and then the second peer review of the rough draft are very helpful but a peer review of the final product would provide that last check that you are on track before submission.  I also think the course work should provide an example of what a good peer review looks like.  There were large variations in from student to student on the peer reviews.