Tuesday, February 13, 2018

It's a Bee; It's an Amphibian, It's a Drone!


One of the topics discussed in this week’s readings was the concept of using micro flying robots and biologically inspired UAS in the future applications. Micro UAS can perform a variety of missions and be used in civilian and military applications. This blog post focuses on these micro flying robots, which are created to resemble insects and even mimic the behaviors of the bugs.

In June 2016, the National Science Foundations published an article “The flight of the RoboBee,” which describes the amazing capabilities of these micro-UAVs, their benefits, and possible applications (Dubrow, 2016). Since then, the micro-UAV development has received much attention due to considerable advances in design and technology. The micro-UAV research aims to create autonomous robotic insects capable of sustained and autonomous flight.

One of the primary applications for the RoboBees is performing crop pollination- the job usually accomplished by the honeybees. Honeybees alone contribute more than $15 billion in value to U.S. crops each year (Spector, 2014). Recently, the honey bee population has been drastically declining due to several factors, such as parasites, disease, and pesticides. If the number of honey bees continues to decline at such an alarming rate, the agricultural sector will feel the negative impacts such as the declining crop volumes. Although the RoboBees technology is still in its development stage, the researchers believe that in less than 10 years these micro-UAVs could artificially pollinate the crops.

Agricultural uses are not the only job micro- UAVs can perform. They are also able to assist in intelligence, surveillance, and reconnaissance (ISR) missions or provide support in remote communications. After natural disasters, the micro-UAVs can assist in search and rescue mission. They can also perform traffic monitoring and law enforcement missions. A swarm of the RoboBees can conduct environmental research, collect data about air contamination (Langston, 2016). However, the flight time of aerial robots is restricted by the weight of their onboard power system and the lifetime of their miniature mechanical components. Additionally, the endurance of current micro-UAS decreases substantially as vehicle scale reduces.

The RoboBees have their strength in numbers. Most of the RoboBees applications will require swarms of thousands of the micro-UAVs working together, autonomously coordinating their operations without relying on a leader- or a “mother-bee.” Large swarm will ensure that the mission will be accomplished even if a large number of single RoboBees fail or fly to recharge themselves. As we can see, the micro-UAV applications are quite diverse.

Now, let’s focus on design and some of the technological features of the RoboBees. The inspiration to create these micro-UAVs came from nature. Insects have the amazing ability to take off, navigate, communicate, and perform precise maneuvers despite their small bodies and tiny brains.
The RoboBee is close to the size of a real bee and weighs only 84 milligrams. Currently, these UAVs are being flown with the use of a tether; however, researchers are working on some advanced control and power solutions for these vehicles. To create these micro flying robots, the researchers had to experiment with compact power storage, ultra-low power computing, artificial muscles, and bio-inspired sensors (Spector, 2014).
The RoboBee is an aerial system, that consists of three main parts: the vehicle, the brain, and the colony (Spector, 2014). The vehicle body is designed to be autonomously flown by using “artificial muscles” made out of materials that contract when a voltage is applied. The UAV should be compact and carry its own power source and all the required sensors.  The “brain” of the micro-UAS is comprised of sensors and control electronics that imitate the eyes and antennae of a bee and can sense and respond to the environment, avoid obstacles and perform agile maneuvering. The Colony component of the system is concerned with managing and coordinating the performance of the independent UAS as a swarm to effectively complete the required mission (Wyss Institute, n.d.).

Figure 1. RoboBee. Adapted from “Tiny flying robots are being built to pollinate crops instead of real bees”, by D. Spector, 2014. Copyright by Wyss Institute.

One of the most challenging aspects of the RoboBee is its power system design.  Many applications for these UAVs would require the RoboBees to perform extended endurance operations. However, one of the disadvantages of a smaller size of the vehicles is their inability to carry enough power for the mission. To give the robot-insects longer endurance, the researchers came up with breakthrough solution- the use perching technique to save energy. This energy conservation behavior is found in other insects, birds, and bats. In the research article “Perching and takeoff of a robotic insect on overhangs using switchable electrostatic adhesion,” by Graule et al., (2016), the researchers incorporated electrostatic adhesion technique — the same principle that causes a static-charged balloon to stick to a wall (Graule et al., 2016) By employing the perching technique, the RoboBee will use about 1000 times less power than during hovering. It will help extend mission time without the need for larger battery incorporation (Burrows, 2016).



Figure 2. RoboBee Perched on the leaf. Adapted from “RoboBees can perch to save energy”, by L. Burrows, L, 2016, Harvard Gazette. Copyright by Wyss Institute.


Figure 3. Perching technique of the RoboBee. Adapted from “Perching and takeoff of a robotic insect on overhangs using switchable electrostatic adhesion,” by M. Graule et al., 2016. Copyright by 2016 Science.  
The perching construction consists of an electrode patch and a foam base that absorbs shock. This modification allows the robot to stick to almost any surface when the electrode patch is supplied with a charge. When the UAV is ready to take off again, the electrical charge is turned off.
Researchers estimate that in the next ten years, the RoboBees will be able to carry out everyday operations. To achieve this goal, they plan to equip these vehicles with new capabilities. The latest generation of micro-bees can also swim. In 2017 the scientists introduced a new and evolved RoboBee which is capable of amphibious operations. In the article “A biologically inspired, flapping-wing, hybrid aerial-aquatic microrobot,” Chang et al., (2017) present the design and operation of micro UAS that is capable of flying, swimming, and transitioning between air and water. The RoboBee uses its wings to swim underwater. When the robot breaks the water surface, the electrolytic plates produce oxyhydrogen from the surrounding water that is collected by a buoyancy compartment. This buoyancy allows the robot to push itself out of the water. A miniature sparker ignites the oxyhydrogen, allowing the UAS to take off from the water surface (Chang et al., 2017).  Future improvement for these microrobots also includes the incorporation of microlaser sensors to aid the bees with better environmental sensing and obstacle avoidance.

The RoboBee project is not only created the amazing micro-UAS, but it also developed new technologies which can be used in other areas. For example, several of the RoboBees principal investigators are now participating in a DARPA-sponsored venture making new surgical tools based on the microfabrication technologies developed in the RoboBees project.


References

Wednesday, February 7, 2018

Unmanned Aerial Systems (UAS) incorporation into the National Aerospace System: Sense-and avoid challenges.


One of the major topics in unmanned vehicles operations is the lack of effective sense-and-avoid (SAA) capabilities of the UAS (Oliver, 2016). A key challenge within the SAA problem is to reliably and automatically detect potential midair aircraft collisions (Bratanov, Mejias, & Ford, 2017).  The ability of the UAS to sense and avoid surrounding traffic must be fully addressed before the UAS can be integrated into the National Aerospace System. As we know, most manned aircraft carry advanced traffic collision avoidance technologies (Federal Aviation Administration [FAA], n.d.). However, UAS are not currently required to incorporate any sense-and-avoid equipment. Piloted aircraft are required to maintain a visual scan for traffic at all times. However, UAS may be difficult to detect due to their small size. Detection is even more difficult in poor meteorological conditions. Since there is no pilot directly at the controls of the UAS, visual traffic detection may be inadequate due to the limited field of view, control signal latency, and other technological constraints. During manned aircraft operations, the pilots are directly responsible to visually detect, avoid, and maintain a safe distance from the surrounding traffic (Consiglio, Chamberlain, Munos, & Hoffler, 2012). Manned aircraft employ a variety of methods for traffic separation. Pilots rely on visual cues, air traffic control (ATC) advisories, and other sensory information available in the cockpit.

The FAA has restricted UAS operations below 400 feet above ground level (AGL), and within the line of sight of the pilot, and in fair meteorological conditions (FAA, 2016). These limitations may help in separating UAS from piloted aircraft to some degree. Nevertheless, these restrictions do not provide the acceptable level of safety. Eventually, UAS missions will have to be extended to altitudes beyond 400 feet AGL and UAS will be operating alongside piloted aircraft in all airspace segments.

The lack of UAS SAA capability and its adverse effects on aviation safety has been a subject of research. The first SAA alternative offered by scholars is a ground-based SAA (GBSAA). This method employs the UAS pilot housed in the ground control station (GCS) as the primary authority for detection, evaluation, and execution of the traffic avoidance maneuvers. The traffic information would be displayed on the screen in the GCS. The UAS pilot will also rely on ATC traffic advisories and alerts and, if necessary, follow the ATC recommendations to avoid the surrounding traffic.

The second alternative action for SAA problem mitigation is to incorporate traffic detecting and avoidance technology directly onboard of the UAS. There are a variety of SAA sensor options available. SAA sensors can be grouped into two categories: cooperative and non-cooperative technologies (Albaker & Rahim, 2011). Cooperative sensors require the installation of transponder equipment on board the aircraft to broadcast its position information and interrogate surrounding traffic (Asmat et al., n.d.). Cooperative sensors will only function if all participating aircraft are equipped with transponders (Fasano, Accardo, Tirri, Moccia, & DeLellis, 2015). On the other hand, non-cooperative sensors are capable to detect airborne targets autonomously, regardless of whether the intruder aircraft carry any SAA equipment or regardless of transponder installation (Asmat et al., n.d.).

A couple examples of cooperative technologies are the Automatic Dependent Surveillance-Broadcast (ADS-B) and the Traffic Alert and Collision Avoidance System (TCAS). ADS-B and is a part of the NexGen ATC system (Zimmerman, 2013).


Figure 1. ADS-B diagram. ADS-B includes ground stations, GPS, and aircraft avionics. Adapted from “ADS-B 101: What is it and why you should care,” by J. Zimmerman, 2013. Copyright 2013 by J. Zimmerman.



Figure 2. TCAS Version 7.1 with smart reversion logic allows pilot to properly select the corrective maneuver, avoid overcorrection, and reverses resolution advisories in accordance with intruder aircraft maneuvering. Adapted from “TCAS II Version 7.1,.” by Eurocontrol, 2014. Copyright 2014 by Eurocontrol.

Another option is to use non-cooperative sensors for UAS SAA. Many researchers have focused more on non-cooperative sensors of the active and passive type as they can provide better detection of the non-cooperative traffic (McClellan, Kang, & Woosely, 2017). There are a variety of technologies currently available, each with its specific advantages and drawbacks (Yu & Zhang, 2015). The main advantage of non-cooperative sensors is their ability to detect the intruder regardless of what equipment is installed on the other aircraft. Therefore, non-cooperative technology is useful if other traffic does not have a transponder or the ADS-B equipment. This sensor category includes the following: thermal, electro-optic/infrared (EO/IR), acoustic, laser obstacle avoidance system (LOAM), millimeter wave radar (MMW), and synthetic aperture radar (SAR).

Sensor fusion is another approach, which combines cooperative and non-cooperative technologies to compensate for limitations of the sensing systems. The research and development in sensors fusion are however still in its initial stages. Using both cooperative and non-cooperative airborne sensor in combination with ground-based traffic surveillance will increase the UAS SAA capability and, therefore, raise the levels of operational safety. Researchers have need testing and suggesting various sensor combinations in different SAA scenarios and evaluating the capabilities of various technology.

Another technological challenge in SAA is to meet the size, weight, and power (SWaP) limitations of UAS and especially small-UAS while still maintaining the needed sensing capability. Some researchers propose the use of miniaturized airborne radar for automated traffic detection and avoidance (Roberts, 2017).

SAA capability should become a major prerequisite for UAS operations in the NAS. SAA capability should be considered a minimum performance requirement for unmanned aircraft. It is important to test the SAA algorithms for different flight scenarios. For example, different aircraft convergence situation should be tested, such as head-on approach, climbing from below, or descending from above. It would be advantageous to perform SAA testing in the various weather conditions. For instance, daylight visual flight rules (VFR) and night VFR. Simulation and actual flight testing should be conducted with different UAS groups to determine that the SAA system meets the required levels of safety (Kuchar, n.d.).

UAS SAA is an overwhelming problem being discussed among aviation regulatory and safety agencies. UAS proliferation is rapidly increasing in the civilian sector, and it is imperative to address a means to incorporate SSA for safe UAS operation. Standardized equipment mandates, UAS certification, and pilot training for SAA scenarios should be established and enforced. Proper standards should be set to assure that UAS collision avoidance performance equals to that of the manned aircraft collision avoidance capabilities. The FAA should revise some of the regulatory documentation to include proper amendments for UAS operations. 

UAS integration into the NAS should not compromise safety or efficiency of the airspace operations. UAS will have to adapt to the standards and procedure currently employed in the NAS. However, it is probable that the current rules and regulations for manned aircraft will have to be adjusted to include the new UAS members. Only then we will be able to take a full advantage of the benefits UAS offer. 



References
Albaker, B. M., & Rahim, N. A. (2011). A conceptual framework and a review of conflict sensing, detection, awareness and escape maneuvering methods for UAVs. Retrieved from UMPEDAC Research Centre, Faculty of Engineering, University of Malaya: http://www.intechopen.com/books/aeronautics-and-astronautics/a-conceptual-framework-and-a-review-of-conflict-sensing-detection-awareness-and-escape-maneuvering-m

Asmat, J., Rhodes, B., Umansky, J., Villlavicencio, C., Yunas, A., Donohue, G., & Lacher, A. (n.d.). UAS safety: unmanned aerial collision avoidance system. Retrieved from http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4055110

Bratanov, D., Mejias, L., & Ford, J. (2017). A vision-based sense-and-avoid system tested on a ScanEagle UAV. International Conference on UAS. https://doi.org/10.1109/ICUAS.2017.7991302
Eurocontrol. (2014). TCAS II Version 7.1. Retrieved from http://www.eurocontrol.int/articles/tcas-ii-version-71

Federal Aviation Administration. (2016). Summary of small unmanned aircraft rule (part 107). Retrieved from http://www.faa.gov/uas/media/Part_107_Summary.pdf

Federal Aviation Administration. (n.d.). 14 CFR 91.227 - Automatic Dependent Surveillance-Broadcast (ADS-B) Out equipment performance requirements. Retrieved from https://www.law.cornell.edu/cfr/text/14/91.227

Kuchar, J. K. (n.d.). Safety analysis methodology for unmanned aerial vehicle (UAVs) collision avoidance systems. Retrieved from Massachusetts Institute of Technology: http://www.ll.mit.edu/mission/aviation/publications/publication-files/ms-papers/Kuchar_2005_ATM_MS-19102_WW-18698.pdf