Interdrone 2015 Notes: Difference between revisions
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From [[Interdrone 2015]] | From [[Interdrone 2015]] | ||
== People == | == 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. | * 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
- Dronekit
- DroneCode
- Driden model (?)
- Stereo Vision (see OpenCV)
- OpenCV
- Gimli Glider
- BeagleBoard - Rasberry Pi Competitor
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
- Ensley Model
- 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.
- Building Situational Awareness
- 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
- Provide metrics on reliability so that the operator knows how well they should trust the system
- Design a system that is trusted and utilized, but not overly trusted so operators become complacent
- 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