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From [[Interdrone 2015]]
From [[Interdrone 2015]]
== Summary ==
There were roughly 3000 individuals, 130 presenters, and over 100 companies present at this year's Interdrone conference. There were dozens of different industries represented, but inspection was, by far, the most prevalent area of interest. Of those already doing inspections, a vast majority were merely doing simple visual inspections (not structural analysis).
The widely overused analogy was that drones in 2015 are what PC computers were in the early 80's. The implication being that now that drones are accessible to everyone, they will revolutionize every industry. While I agree that the technology has huge potential in certain applications, this industry is still very immature and it will take years to stabilize the hardware, software, and regulations surrounding the industry.
Not surprisingly, the FAA is extremely uneasy about the introduction of this disruptive technology into national airspace. They understand that drones have the potential to revolutionize certain industries, but are struggling to determine how to best regulate them. Existing regulations obviously were not written with unmanned aircraft in mind and do not explicitly prohibit their use.
Many drone-based companies had already taken advantage of this ambiguity and were operating with no oversight. In order to wrestle back control, the FAA sighted FAR 91.113 which states:
<pre>vigilance shall be maintained by each person operating an aircraft so as to see and avoid other aircraft.</pre>
Obviously an unmanned aircraft cannot inherently "see and avoid" and, therefore, according to the FAA, now require an exemption. 
<pre>The 333 Exemption process "grants case-by-case authorization for
certain unmanned aircraft to perform commercial operations. It provides
operators who wish to pursue safe and legal entry into the NAS a competitive
advantage in the UAS marketplace, thus discouraging illegal operations and
improving safety.</pre>
These exemptions look very much like an Ops Spec, and outline exactly who can operate the aircraft (with a pilot's license), what make and model of aircraft can be used, and any limitations that should be in place (see [https://www.faa.gov/uas/legislative_programs/section_333/333_authorizations/media/Aeronautic-Imagery-LLC-12794.pdf this]). The FAA has granted roughly 1500 exemptions to companies across the US and has hundreds more waiting to be processed. The typical exemption takes between 50 and 190 days to be approved (depending on complexity and risk).
In addition to a 333 exemption, companies may be required to request a Certificate of Waiver or Authorization (COA). This waiver provides operators with permission to operate unmanned aircraft.


== People ==
== People ==


* Diane
* Dyan Gibbens - currently owns two drone-based companies. I was very impressed with Dyan and think she could be a valuable consultant in assisting with the regulatory challenges.
* Jim Williams - former FAA employee that wrote much of the new regulation regarding UAVs.
* Jim Williams - former FAA employee that wrote much of the new regulation regarding UAVs.


Latest revision as of 16:11, 22 September 2015

From Interdrone 2015

People

  • Dyan Gibbens - currently owns two drone-based companies. I was very impressed with Dyan and think she could be a valuable consultant in assisting with the regulatory challenges.
  • Jim Williams - former FAA employee that wrote much of the new regulation regarding UAVs.

Areas for Further Research

Crowd Analytics through Facial Recognition

Eyeris

Software package called ImoVu - Deep Learning architecture for image processes that imitates human recognition

  • Vision for Embedded Systems
  • 97% accurate
  • 140 FPS on i7 processor
  • Ambient Intelligence (AML) - Electronic environments that are sensitive and responsive to the presence of people.
  • Minimal required resolution for a face: 50x50px, Ideal 70x70px
  • Does not use FACS
  • Uses OpenCV open source software to identify faces and for some devices, sometimes falls back to the devices facial recognition
  • This software is not useful for things or places (only people)
  • Allows for
    • Access to Hard to reach places
    • Large coverage area
    • Eye Level
    • Improved angles


  • Trained For
    • 5 Major ethnic groups
    • 5 age groups
    • 2 genders
    • 10 lightning conditions
    • 13 head poses
    • supervised and unsupervised
    • different camera structures
    • different resolution
    • different face attributes
      • Joy
      • Surprise
      • Sadness
      • Disgust
      • Anger
      • Fear
      • Neutral

3D Mapping

  • mark@visuallaw.com
  • sketchfab - 3d modeling software
  • pointcloud
  • DroneDeploy - android app for creating 3d mesh and orthomap ($300 a month)
  • Pix4D - the primary software for creating 3 modeling of terrain
  • Adjisoft Photoscan (?) - Competitor to pix4d
  • Autodesk is working on comparable software

DroneKit

Flying in Wind: State Estimation for UAS

  • Douglas Weibel, PHD
  • Wind - a vector velocity field with spatial and temporal variation
  • Wind has structured (predictive) and random properties (turbulence) that are difficult to model
  • State
    • Attitude (Roll, Pitch, Yaw, Roll Rate, Pitch Rate, Yaw Rate)
    • Attitude Rates
    • Position
    • Velocity
  • Other possible states
    • Wind Paramters
    • Height over ground
    • Battery energy
    • gyro bias
    • accel bias
  • Attitude Estimation
    • Stabilized Sub Platform
    • Whabba's problem
    • Integration
    • Combined
  • Contempory Sensors
    • Gyros
    • Accelerometers
    • Magnetomers
    • GPS Baseline
    • Thermopile
    • Elecstratic potential
    • Opical sensors
  • Federated Filter
  • Attitude Filter ( Cascaded Filter )

Applications of Rotation Matrices and Matrix-Vector Algebra in Autopilots

Bill Premerlani

  • A rotation matrix is a linear homegeneous transformation
  • Tensor

FAA Regulations: Past, Present, and Future

  • Jim Williams
  • Drones are named from the first unmanned aircraft in Britain during WW1
  • [1]
  • FAA cant regulate anything congress doesn't give them authority over
  • Required for an aircraft to be regulated
    • Approved Pilot
    • Aircraft Certificate
  • Code of Federal Regulations (91.113) - you must be able to see and avoid other aircraft (thus-- you need a 333)
  • COWA - Certificate of Waiver or Authorization
  • AC - 91.57A new AC that regulates RC hobby
  • AC's are not regulatory
  • CFR 14 91.13 Careless and Reckless Operation
    • Aircraft operations for the purpose of air navigation. No person may operate an aircraft in a careless or reckless manner so as to endanger the life or property of another.
    • Don't do stupid things that put people in the air at risk.
  • 14 CFR Part 107 creates new rules for small unmanned aircraft systems
  • Examples
    • CNN is looking at tethered aircraft (tether provides power) - Power Electronics 01
    • Railroad wants UAV to monitor tracks in front of trains looking for issues with tracks
    • Farmers are looking for ways to safely use UAV without LOS by monitoring airspace for incoming commercial aircraft
  • FAA - Department of Transportation interactions take a lot of time
  • Most insurance policies will not cover accidents caused by commercial use of drones
  • Some companies with 333 exemptions are suing companies operating without the proper exemptions

Embedded Computer Vision for Safer, Faster Drones

  • Goksel Dedeoglu, Founder PercepTonic, LLC
  • Computer vision algorithms analyze images to extract information about the world (allowing machines that perceive)
    • Size and shape
    • 3d position
    • Identity
    • Expression
    • Location
    • Motion
    • Illumniation, weather, etc.
  • Two things relevant for drone operation:
    • Motion
    • Depth
  • Inertial sensors
    • Identifies key points
  • GerbilBall is a safety sphere enabled by real-time depth sensing
    • Stereo-based
    • Has limitations on how close the two objects can be to each other
    • Can have as many cameras as needed to create a realtime look in all directions (expensive)
    • For objects that don't move often, may be cheaper to build an internal model of what has been seen
  • Best guess for power efficient vision computation is heterogeneous and multi-core architechtures
  • Examples
    • Fire Phone makes good use of computer vision with multiple cameras
    • Dyson 360 Roomba
  • http://www.cvisioncentral.com/evw2015
  • http://www.embedded-vision.com

DroneKit

  • A single API that runs onboard drones
    • Cloud REST API
    • Android SDK ("3DR Services")
    • Python SDK
  • Dronekit exists as a compatibility layer on top of the autopilot
  • Onboard and offboard MAVLink
  • Droneshare.com
    • REST API (speaks JSON)
    • Used for storing fetching displaying logs and other data
  • Full autopilot control from mobile
  • Built on Android AIDL infrastructure
  • Examples
    • Tower, DroidPlanner, Tower Pebble, Tower Wear, Solo
  • DK Python
  • "Solo is the best tool for aerial video".
    • Runs on PixHawk 2 (unreleased)
    • SDK for Solo dev.3dr.com
      • Prototype in Python without low level system knowledge


  • Pixhawk
  • tim@3dr.com

Structural Inspections

  • 6 weeks to 190 days to get 333
  • Several of the participants have run into issues with RF interference. One person had a fly away in downtown LA. It was identified as interference caused by a nearby consumer WIFI device. One person recommended an RF analysis as part of the pre-flight.
  • Military-grade components have much better shielding and seem to handle interference better.

Human Factors

  • Alexander Stimson - alex@autonometrics.com *
  • In order to keep from overwhelming the operator
    • Multimodal - Use things like sound, or LEDS, to indicate status
  • Multiple HSC Tasks = divided attention problem - most people don't multitask well
    • Encourage task switching efficiency
    • Minimize the switching costs
    • Ensure that the operator is focused on the appropriate tasks
      • Procedures
      • Structure based abstractions - colors, arrows, etc.
      • Automation Cueing
      • Cues/alerts should be appropriate and not overwhelming. There is a cognitive cost to processing cues. Don't make the problem worse.
      • Consider Interruption Lag cueing-- an early warning about something that will eventually become important (the upcoming block in tetris) - studies are not conclusive on effectivity
      • Increase role of automation
      • Provide stopping rules - let the operator know when to move on
  • Humans are not rational decision makers
  • Three general classes of heuristics
    • Representative - humans are generally insensitive to prior probability (what happened yesterday)
    • Anchoring - early assumptions have more weight than new information
    • Availability -
  • Bias
    • Confirmation Bias - once a hypothesis has been made, people tend to try and support it
    • Assimilation Bias - once a hypothesis has been made, new evidence tends to be bias towards that hypothesis
    • Automation Bias - when you have an autonomous system, people tend to give it too much weight
  • Supervisory Monitoring of Operations - System identifies that the operator is overwhelmed
    • Use metrics to identify poor performance
    • Can be human or automated
    • How to handle an overloaded operator
      • Notifiy the operator
      • Redistribute task load to other team members
      • Bring in more team members
      • Modify the mission objectives (accept it)
  • Distributed Decision Making
    • Building Situational Awareness
      • Ensley Model
        • Perception
        • Comprehension
        • Projection
    • Use Collaboration to Increase SA
      • Same time and place - face to face
      • Same Time/Different Place - radio/video
      • Different Time/Different Place - email, text
      • Different Time/Same Place - log books, etc.
  • Trust and Reliability
    • Design a system that is trusted and utilized, but not overly trusted so operators become complacent
      • Provide metrics on reliability so that the operator knows how well they should trust the system
        • Is it raining?
        • How reliable are my sensors?
        • What resolution is the data
        • Number of active satellites
      • Keep metrics frequent and appropriate
        • Don't show old information that doesn't matter anymore
  • Role of Automation
    • There are different levels of automation (1-10) from operator does nothing to operator is overworked
    • The level may need to change depending on the operators effectivity
    • Use cuing
      • Environment (time/event)
      • Psychophysiological
      • Performance metrics
  • Accountability
    • Don't shoot kids!

Fuzzy Logic Control Systems for Fixed-Wing Drones

  • FLC provide a simpler method for controlling fixed wing aircraft
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