Quoting from a widely distributed email. I work on one UAS ASTM effort to type Small UAS. Here are their other efforts. Of particular interest is F2908 “Specification for Aircraft Flight Manual (AFM) for a Small Unmanned Aircraft System (sUAS).”
Small UAS Operations
ASTM International Committee F38 on Unmanned Aircraft Systems has recently approved seven new standards that cover all major facets of small unmanned aircraft systems operations, including design, construction, operation and maintenance requirements.
The following seven new ASTM standards, written for all sUAS that are permitted to operate over a defined area and in airspace defined by a nation’s governing aviation authority, have now been approved by F38:
F2908, Specification for Aircraft Flight Manual (AFM) for a Small Unmanned Aircraft System (sUAS). F2908 defines minimum requirements for the aircraft flight manual, which provides guidance to owners, mechanics, pilots, crew members, airports, regulatory officials and aircraft and component manufacturers who perform or provide oversight of sUAS flight operations.
F2909, Practice for Maintenance and Continued Airworthiness of Small Unmanned Aircraft Systems (sUAS). F2909 establishes a practice for the maintenance and continued airworthiness of sUAS. Requirements for continued airworthiness, inspections, maintenance and repairs/alterations are included.
F2910, Specification for Design and Construction of a Small Unmanned Aircraft System (sUAS). F2910 defines the design, construction and test requirements for sUAS. In addition to general requirements, F2910 covers requirements for structure, propulsion, propellers, fuel and oil systems, cooling, documentation and other key areas.
F2911, Practice for Production Acceptance of Small Unmanned Aircraft System (sUAS). F2911 defines production acceptance requirements for sUAS. Requirements covered include several aspects of production, system level production acceptance, quality assurance and documentation.
F3002, Specification for Design of the Command and Control System for Small Unmanned Aircraft Systems (sUAS). F3002 provides a consensus standard in support of an application to a nation’s governing aviation authority to operate an sUAS for commercial or public use. The standard focuses on command and control (C2) links, including a diagram of a C2 system and general requirements for C2 system components.
F3003, Specification for Quality Assurance of a Small Unmanned Aircraft System (sUAS). F3003 defines quality assurance requirements for design, manufacture and production of small unmanned aircraft systems. Guidance is given to sUAS manufacturers for the development of a quality assurance program.
F3005, Specification for Batteries for Use in Small Unmanned Aircraft Systems (sUAS). F3005 defines requirements for battery cells used in sUAS. Mechanical design and safety, and electrical design battery maintenance are primary battery-related areas that are covered.
“The introduction of these standards developed by F38 will help to provide a safe and appropriate path for near-term routine sUAS operations in airspace systems of the United States and other countries,” says Theodore Wierzbanowski, chairman F38.
Committee F38 encourages participation in its standards developing activities. “The user community for these standards is vast,” says Wierzbanowski. “Feedback on what works and what doesn’t during these early stages of sUAS operation is critical.”
F2908 is under the jurisdiction of F38.03 on Personnel Training, Qualification and Certification, and F2909 was developed by F38.02 on Flight Operations. The other five new standards are under the jurisdiction of F38.01 on Airworthiness.
UAS, unmanned aerial systems, can play a significant role in search and rescue (SAR) operations. There are a number of hurdles to deploying these assets successfully. In my role as advocacy director for the National Association of Search and Rescue (NASAR) I’ve written position papers to address two of the hurdles:
- UAS deployment in support of SAR (and other disaster response incidents) requires professional UAS operators. At the present time, that means that all UAS operations must be performed under a valid COA either by public agencies or by Section 333 exempt operators. I wrote a paper for NASAR explaining this position and how public agencies and SAR volunteers can fly in support of SAR missions while complying with FAA policy/rules/guidelines.Here is the NASAR announcement which includes a link to the paper.
- Current FAA policy places three significant restrictions on UAS operations that make deployments extremely difficult and very ineffective:
- The operator must issue a NOTAM 72 hours before flying. (SAR is an emergency. UAS assets are extremely helpful in the early stages. Search is an emergency.)
- The operator must fly at or below 200 feet. (Imaging wide swaths of the area, operating in hilly or mountainous terrain, or establishing a communications relay with wide area coverage, requires higher altitudes.)
- The operator must not fly any closer than 500 feet to non-participating individuals or property. (Search subjects do not go missing in areas with zero population and no structures.)
To address these issues, Jason Kamdar and I wrote a proposal for a “First Responder COA (FRCOA)” to submit to the FAA. The document can be found here and the NASAR announcement about the paper and other related activity is here.
The title is intentionally provoking. Too many public comments are similar to “A falling drone will give you a bump on the head”. In fact, there is a reasonable chance it will kill you. Which of these is actually true? We simply do not know and some formal experiments are required before claims are made either way. So my point is not really that they may kill you, rather it is that we need good data.
I’d like to thank the members of a particular Facebook group for engaging in a spirited discussion that helped me refine this post. It was far too provocative in the early draft and I am certain that it still is for some.
The theoretical analysis follows, and it ignores a lot of variables. These calculations are a starting point and represent the “worst case scenario”. With a lot of additional work, we could add other constraints and end up with a probability estimate of damage from a direct impact.
Weight of a DJI Phantom – 1242g (2.73 lbs)
Altitude at time of failure – 61m (200 feet)
Force required to crush a human skull – 2,300N (Journal of Neurosurgery: Pediatrics)
Let’s plug those numbers into a calculator:
7173N of force. Almost three times the force required to crush a human skull.
Even from half that height, 100 feet, a falling Phantom would generate 3527N, still enough to crush your skull. At 65 feet you might survive the impact as the force is down to 2351N.
There are a lot of variables that I did not account for – drag, impact angle, elasticity in the body and the drone…. Real experiments need to be performed.
In an earlier post I wrote: “I think the search & rescue community should do a lot more work on designing and performing experiments with UAVs. Vendors and sales outlets keep touting their UAVs as being “good for search & rescue” without providing any data to support this claim, and often without really understanding SAR, SAR missions, and the challenges we face. (More on this in my upcoming presentation for NAASIC in Reno in September.)”
This is even more important when we consider what are appropriate missions for UAVs and how to deploy them.
I conducted two very quick experiments to illustrate two of the challenges we face. I intend to develop more formal experiments and welcome others who are interested in assisting with this effort.
I wanted to answer two questions:
- How effective is a UAV when searching an area with trees?
- How effective is a UAV when searching for clues in a soybean field?
Both of these are simple examples of SAR problems you can adapt to your own operational area.
tl;dr – You need to be down very low when searching near trees and finding an unresponsive subject in a soybean field with an optical sensor is very tough.
Searching Near Trees:
If this was your search area, and if you were searching for an uncooperative or unresponsive subject (someone who isn’t going to come investigate the noise of the UAV), how would you plan your mission? How would you execute it? How long would it take? How effective would you be? (This was taken at 200 feet by a Phantom Vision 2+. The subject is currently in the frame.)
Ok, if the subject were standing under a tree in this small area, what would you be able to see? (There are a lot of variables here – height of branches, folliage on or off, distance from subject, subject’s distance from the trunk, …. This is just an example.)
Distance from the UAV to the subject was less than 50 feet in all images.
At the subject’s altitude:
At about a 30 degree angle:
50 degrees. The subject’s legs are barely visible due to the contrast between his blue jeans and the green background. (And, if you were looking at this on a mobile device, what would you really be able to see?)
70 degrees or so. The subject is not visible.
Conclusion – you need to get under the level of the tree branches to search around trees for an unresponsive subject. This will increase your time required to search while diminishing your ability to control the UAV at long ranges.
I live, and search, in Illinois. Lots of corn, lots of soybeans. Searching for anyone in a corn field when the corn is above your head is tough. We’ll come back to that one later. Soybeans get to a few feet tall. Walking through soybean fields is … annoying … but you can certainly see a lot more. If the subject is standing up you can just walk to the edge of the field and say “Hey, there they are!” But, what if they are unresponsive and down?
Again, 50 feet up with a DJI Phantom Vision 2+. The subject dropped their high visibility orange shirt, a clue! We can see it easily on the edge of the field.
But, what if they dropped it in the field? Since you know it is in the frame, and since it is right next to the pilot, you can probably see it. If you were looking at images from 100 acres of soybeans how confident are you that you’d see this clue, particularly on a small screen?
If you are using a normal consumer UAV to search for an unresponsive subject in an area with significant vegetation your probability of detection may be rather low.
I think the UAV industry in general and the search & rescue community in specific should do a lot more work on designing and performing experiments with UAVs. Vendors and sales outlets keep touting their UAVs as being “good for search & rescue” without providing any data to support this claim, and often without really understanding SAR, SAR missions, and the challenges we face. (More on this in my upcoming presentation for NAASIC in Reno in September.) On the privacy side, people claim “he couldn’t see anything at 200 feet with that drone.” or the opposite position without sharing any data to support these claims.
Since I am an engineer, I like to gather data to support conclusions. And, for similar reasons, I usually form a hypothesis prior to conducting an experiment. Full disclosure – the data did not support my hypothesis. I’ll explain at the end of this post.
For the tl;dr folk – you cannot see much detail in a stock Phantom 2 Vision+ image when taken more than 50 feet above the subject.
This experiment was conducted with a stock DJI Phantom 2 Vision+. The lens specifications, according to DJI, are:
- Sensor Size – 1/2.3″
- Effective Pixels – 14 Megapixels
- Resolution – 4384×3288
- Recording FOV -110° / 85°
I had the camera set to use the “large” photo size and thus the full resolution.
The items in the frame are:
- A black Pelican case
- A human male wearing blue jeans and a reddish t-shirt
- A high visibility orange long sleeve thermal shirt
- A light blue t-shirt
- A white board with black writing on it
The sky was overcast and the winds were between 5 and 15mph out of the south east. I took the Phantom up to 25, 50, 100, 150, 200, 250, and 300 feet, +/- 3 feet as reported by DJI’s Vision app. At each altitude I took a single photograph. After landing, I used Photoshop to zoom in to approximately the same area in each image.
In the raw images viewed natively without any zoom:
- It is hard to find any identifying details of a human in the image above 50 feet.
- At 200 feet it would be hard to identify the human if you did not know what you are looking at.
Using the zoom tool in Photoshop:
- Detail is hard to discern at 100 feet and very difficult past 100 feet
- Given the subject’s pose you can determine that there is a human in the frame up to 300 feet.
- If you thought a drone would be invading your privacy when flown at 200 feet do you still feel this way after looking at these images?
- If you want to use a drone to search for missing people, do these images help you determine your mission parameters and effectiveness?
And my hypothesis? I thought more detail would be available further up. Glad I’m conducting experiments.
Image analysis is not my forte. If you have additional observations, please comment or share them with me directly and I’ll get them included.
I’ve been giving a presentation on the fundamentals of UAV forensics for several months, primarily for law enforcement and for other cyber security people. The presentation was recorded last month and is available on line.
50 minutes long but probably worth watching if you are interested in such things.
On July 17th, 2015, we were asked by the Tazewell County Emergency Management Agency to fly a UAV mission to collect aerial imagery to be used for damage assessment and storm severity determination. Within an hour of the request, we were on scene. All of the imagery was collected within two hours and Pekin’s GIS department processed and hosted the imagery within two additional hours. Call out to online imagery was five hours. Additional area to be covered would not have significantly impacted the total time required.
The ability to perform rapid deployment, collection and analysis workflows is crucial in emergency management settings. Our attention to processes, procedures, training, and relationships enabled us to perform this work efficiently and safely.
The swipe map version of the imagery can be found here.