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SLAM aware applications
by Kuldeep Singh, Raju Kandaswamy, ARVR Practice
© 2019 ThoughtWorks
Know your
surroundings
What do you see around you?
2© 2019 ThoughtWorks
Map the area!
Know your location
Where are you?
3© 2019 ThoughtWorks
Your location in the map
Table of Content
● SLAM Overview
● Approaches of SLAM
● Usage of SLAM
● ARVR & SLAM
4© 2019 ThoughtWorks
SLAM OVERVIEW
5© 2019 ThoughtWorks
Simultaneous
Localization And
Mapping(SLAM)
SLAM technology knows the agents
location in the surrounding and at same
time learn the map.
SLAM aware applications have access to
location and the map.
KEEP TRACK OF THE MAP AND LOCATION
6© 2019 ThoughtWorks
7
SLAM aware apps -
Crawl and Learn
Crawl thru the sea objects, learn and
recognize them:
- Self driving car
- Indoor positioning
- Augmented Reality Spatial
computing
Search engine of the physical world
8© 2019 ThoughtWorks
SLAM is an estimation
technique
SLAM is the technique to simultaneously
do following estimations :
● Pose estimation - Determining the
position and orientation of the agent
(camera) relative to the object (or
vice-versa).
● Map estimation - Estimate the
locations of the objects in the
environment.
9© 2019 ThoughtWorks
Why SLAM is difficult?
10© 2019 ThoughtWorks
● Pose estimation - Needs object’s
locations in the environment i.e Map.
● Map estimation - Needs information
on agent pose (camera pose) to
estimate object’s position.
Approaches of SLAM
11© 2019 ThoughtWorks
SLAM problem definition
12
SLAM is a process by which a mobile
device can build a map of an
environment and at the same time
use this map to deduce it’s location.
In SLAM both the trajectory of the
platform and the location of all
landmarks are estimated real time
without the need for any a prior
knowledge of location.
SLAM approaches
● EKF (Extended Kalman Filter) SLAM
● FastSLAM
● L-SLAM (Matlab code)
● GraphSLAM
● Parallel Tracking and Mapping
(PTAM)
● MonoSLAM
● CoSLAM
● SeqSlam
● iSAM (Incremental Smoothing and
Mapping)
● CT-SLAM (Continuous Time)
From mid eighties to now, a variety of approaches are there, solving it to a certain approximation
13
Open Source
● LSD-SLAM
● S-PTAM
● ORB-SLAM
● Google Cartographer
www.openslam.org
A deep dive one approach
Basic Functional EKF-SLAM Pseudo Code
14
%INITIALIZATION
initialize_map()
While (execution() == true) do
control = acquire control signal()
move device(control)
% LOOP SENSORS IN DEVICE
for each sensor in device−>list of sensors
raw = sensor−>acquire raw data()
% LOOP OBSERVATIONS IN EACH SENSOR
for each observation in sensor−>feasible observations()
% MEASURE LANDMARK AND CORRECT MAP
measurement = find known feature(raw, observation)
update map(sensor, landmark, observation, measurement)
end
% DISCOVER NEW LANDMARKS WITH THE CURRENT SENSOR
measurement = detect new feature(raw)
% INITIALIZE LANDMARK
landmark = init new landmark(robot, sensor, measurement)
create new observation(sensor, landmark)
end
end
Usage of SLAM
15© 2019 ThoughtWorks
Usage of SLAM
16© 2019 ThoughtWorks
Autonomous Vehicle - Space, Air, Earth, under the earth, under water
Usage of SLAM
17© 2019 ThoughtWorks
Autonomous Vehicle - vacuum cleaner, lawn mower, automated warehouse, robots
Usage of SLAM
18© 2019 ThoughtWorks
Augmented Reality & Virtual Reality
ARVR & SLAM
19© 2019 ThoughtWorks
20© 2019 ThoughtWorks
● Development Tools
○ Android (NDK)
○ ARCore SDK
○ Unity
○ Vuforia
○ Wikitude
○ Unreal
● SLAM
○ Concurrent odometry
and mapping
● Sensors - IMU
● Features
○ Motion tracking
○ Light estimation
○ Feature points
○ Cloud Anchors
Android Phone and Tablets iOS Phone and Tablets
● Development Tools
○ ARKit SDK
○ Unity
○ Vuforia
○ Wikitude
○ Unreal
● SLAM
○ Visual Inertial Odometry
● Sensors - IMU
● Features
○ Motion tracking
○ People Occlusion
○ Multi camera, face
tracking
Head Mounted Display - Mixed Reality
21© 2019 ThoughtWorks
Microsoft HoloLens
● Development Tools
○ Universal Windows Platform (UWP)
○ Mixed Reality ToolKit (MRTK)
○ DirectX custom engine
○ Unity
○ Unreal
● SLAM
○ Custom PTAM
● Sensors
○ IMU( Accelerometer, Gyroscope)
● Features
○ Motion tracking
○ Spatial mapping and sound
○ Scene detection and storage
Head Mounted Display - Mixed Reality
22© 2019 ThoughtWorks
Magic Leap One
● Development Tools
○ Lumin SDK
○ Unity
○ Unreal
● SLAM - Deep CNN
○ Magic Point
○ MagicWarp
● Sensors
○ Lightwear IMU( Accelerometer, Gyroscope)
○ EM tracking
○ Controller IMU
● Features
○ Motion tracking
○ Spatial mapping
Head Mounted Display - Virtual Reality
23© 2019 ThoughtWorks
Oculus Quest
● Development Tools - Android
○ Oculus Quest Native SDK
○ vrAPI (Native Engine)
○ Unity
○ Unreal
● SLAM - Oculus Insight
○ LSD-SLAM: Large-scale direct monocular SLAM
○ ORB-SLAM
● Sensors
○ Multiple IMU( Accelerometer, Gyroscope)
○ Infrared
○ Camera
Way to go...
24© 2019 ThoughtWorks
● Web based SLAM is still to be explored.
● Visual SLAM has a lot of environmental limitations
● AI advancements will take the journey further
● Small footprint algorithm are being built to run on small devices
Visit Us @ ARVR Stall
THANKYOU
25
RAJU KANDASWAMY
ARVR Practice
raju.kandaswamy@thoughtworks.com | thoughtworks.com
© 2019 ThoughtWorks
KULDEEP SINGH
ARVR Practice
kuldeeps@thoughtworks.com | thoughtworks.com

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Slam aware applications

  • 1. 1 SLAM aware applications by Kuldeep Singh, Raju Kandaswamy, ARVR Practice © 2019 ThoughtWorks
  • 2. Know your surroundings What do you see around you? 2© 2019 ThoughtWorks Map the area!
  • 3. Know your location Where are you? 3© 2019 ThoughtWorks Your location in the map
  • 4. Table of Content ● SLAM Overview ● Approaches of SLAM ● Usage of SLAM ● ARVR & SLAM 4© 2019 ThoughtWorks
  • 5. SLAM OVERVIEW 5© 2019 ThoughtWorks
  • 6. Simultaneous Localization And Mapping(SLAM) SLAM technology knows the agents location in the surrounding and at same time learn the map. SLAM aware applications have access to location and the map. KEEP TRACK OF THE MAP AND LOCATION 6© 2019 ThoughtWorks
  • 7. 7
  • 8. SLAM aware apps - Crawl and Learn Crawl thru the sea objects, learn and recognize them: - Self driving car - Indoor positioning - Augmented Reality Spatial computing Search engine of the physical world 8© 2019 ThoughtWorks
  • 9. SLAM is an estimation technique SLAM is the technique to simultaneously do following estimations : ● Pose estimation - Determining the position and orientation of the agent (camera) relative to the object (or vice-versa). ● Map estimation - Estimate the locations of the objects in the environment. 9© 2019 ThoughtWorks
  • 10. Why SLAM is difficult? 10© 2019 ThoughtWorks ● Pose estimation - Needs object’s locations in the environment i.e Map. ● Map estimation - Needs information on agent pose (camera pose) to estimate object’s position.
  • 11. Approaches of SLAM 11© 2019 ThoughtWorks
  • 12. SLAM problem definition 12 SLAM is a process by which a mobile device can build a map of an environment and at the same time use this map to deduce it’s location. In SLAM both the trajectory of the platform and the location of all landmarks are estimated real time without the need for any a prior knowledge of location.
  • 13. SLAM approaches ● EKF (Extended Kalman Filter) SLAM ● FastSLAM ● L-SLAM (Matlab code) ● GraphSLAM ● Parallel Tracking and Mapping (PTAM) ● MonoSLAM ● CoSLAM ● SeqSlam ● iSAM (Incremental Smoothing and Mapping) ● CT-SLAM (Continuous Time) From mid eighties to now, a variety of approaches are there, solving it to a certain approximation 13 Open Source ● LSD-SLAM ● S-PTAM ● ORB-SLAM ● Google Cartographer www.openslam.org
  • 14. A deep dive one approach Basic Functional EKF-SLAM Pseudo Code 14 %INITIALIZATION initialize_map() While (execution() == true) do control = acquire control signal() move device(control) % LOOP SENSORS IN DEVICE for each sensor in device−>list of sensors raw = sensor−>acquire raw data() % LOOP OBSERVATIONS IN EACH SENSOR for each observation in sensor−>feasible observations() % MEASURE LANDMARK AND CORRECT MAP measurement = find known feature(raw, observation) update map(sensor, landmark, observation, measurement) end % DISCOVER NEW LANDMARKS WITH THE CURRENT SENSOR measurement = detect new feature(raw) % INITIALIZE LANDMARK landmark = init new landmark(robot, sensor, measurement) create new observation(sensor, landmark) end end
  • 15. Usage of SLAM 15© 2019 ThoughtWorks
  • 16. Usage of SLAM 16© 2019 ThoughtWorks Autonomous Vehicle - Space, Air, Earth, under the earth, under water
  • 17. Usage of SLAM 17© 2019 ThoughtWorks Autonomous Vehicle - vacuum cleaner, lawn mower, automated warehouse, robots
  • 18. Usage of SLAM 18© 2019 ThoughtWorks Augmented Reality & Virtual Reality
  • 19. ARVR & SLAM 19© 2019 ThoughtWorks
  • 20. 20© 2019 ThoughtWorks ● Development Tools ○ Android (NDK) ○ ARCore SDK ○ Unity ○ Vuforia ○ Wikitude ○ Unreal ● SLAM ○ Concurrent odometry and mapping ● Sensors - IMU ● Features ○ Motion tracking ○ Light estimation ○ Feature points ○ Cloud Anchors Android Phone and Tablets iOS Phone and Tablets ● Development Tools ○ ARKit SDK ○ Unity ○ Vuforia ○ Wikitude ○ Unreal ● SLAM ○ Visual Inertial Odometry ● Sensors - IMU ● Features ○ Motion tracking ○ People Occlusion ○ Multi camera, face tracking
  • 21. Head Mounted Display - Mixed Reality 21© 2019 ThoughtWorks Microsoft HoloLens ● Development Tools ○ Universal Windows Platform (UWP) ○ Mixed Reality ToolKit (MRTK) ○ DirectX custom engine ○ Unity ○ Unreal ● SLAM ○ Custom PTAM ● Sensors ○ IMU( Accelerometer, Gyroscope) ● Features ○ Motion tracking ○ Spatial mapping and sound ○ Scene detection and storage
  • 22. Head Mounted Display - Mixed Reality 22© 2019 ThoughtWorks Magic Leap One ● Development Tools ○ Lumin SDK ○ Unity ○ Unreal ● SLAM - Deep CNN ○ Magic Point ○ MagicWarp ● Sensors ○ Lightwear IMU( Accelerometer, Gyroscope) ○ EM tracking ○ Controller IMU ● Features ○ Motion tracking ○ Spatial mapping
  • 23. Head Mounted Display - Virtual Reality 23© 2019 ThoughtWorks Oculus Quest ● Development Tools - Android ○ Oculus Quest Native SDK ○ vrAPI (Native Engine) ○ Unity ○ Unreal ● SLAM - Oculus Insight ○ LSD-SLAM: Large-scale direct monocular SLAM ○ ORB-SLAM ● Sensors ○ Multiple IMU( Accelerometer, Gyroscope) ○ Infrared ○ Camera
  • 24. Way to go... 24© 2019 ThoughtWorks ● Web based SLAM is still to be explored. ● Visual SLAM has a lot of environmental limitations ● AI advancements will take the journey further ● Small footprint algorithm are being built to run on small devices Visit Us @ ARVR Stall
  • 25. THANKYOU 25 RAJU KANDASWAMY ARVR Practice raju.kandaswamy@thoughtworks.com | thoughtworks.com © 2019 ThoughtWorks KULDEEP SINGH ARVR Practice kuldeeps@thoughtworks.com | thoughtworks.com

Editor's Notes

  1. 30 Sec SLAM is about - knowing your surrounding and mapping it. “What do see around you”? Door, Wall, Floor, Stage, People around you. Sense of depth Who is front of other Map of the area
  2. 30 Sec Next key thing in SLAM is Localization - Know your location in the map you have created in earlier You are in between these I am on stage I am seating at x seat etc
  3. 30 Sec Now doing all together Move around the room Map and localize Move again map and localize What is SLAM aware applications or systems? Where you have access to location and this map. -
  4. 1Min Another way to explain SLAM is a system which crawl and learn. - a search engine. Eg. When you reach home, you place your car keys/or belongings at key tray, and next day I ask my mind where is car key, I got the answer. Essentially, so we are talking about building eye which helps record data and the processing unit and search engine, your mind.
  5. Handing to Raju to discuss some techniques and solutions of SLAM. https://en.wikipedia.org/wiki/List_of_SLAM_Methods
  6. http://ais.informatik.uni-freiburg.de/teaching/ss12/robotics/slides/12-slam.pdf https://github.com/googlecartographer https://en.wikipedia.org/wiki/List_of_SLAM_Methods
  7. http://www.iri.upc.edu/people/jsola/JoanSola/objectes/curs_SLAM/SLAM2D/SLAM%20course.pdf
  8. Handover to speaker 1
  9. https://patent.yivian.com/3339.html
  10. Visual SLAM https://ai.facebook.com/blog/slam-bringing-art-to-life-through-technology/
  11. https://developers.google.com/web/updates/2018/06/ar-for-the-web