Slides for Virtual Reality Meetup bei https://innfactory.de am 02.05.2018 von Sebastian Appelt

1. Virtual Reality
Meetup in(n) Factory
Sebastian Appelt, 02.05.2018

2. 2
1. Introduction to VR/AR
2. Application Scenario: Smart Factory
3. Demo Videos
Outline

3. 3
Hi!
Sebastian Appelt
 Innovation specialist
 Machine Learning, AI, Virtual Reality, Blockchain, Full Stack Dev, Quantum
Computing
 Studying @LMU and working @NTT Data / Enso

4. 1 Introduction to VR/AR

5. 5
 Project virtual objects into the real environment
Augemented Reality

6. 6
 Immersive experience in a virtual world
Virtual Reality

7. 7
How does it work?

8. 8
Devices
HTC Vive Oculus Rift Microsoft Hololens

9. 9
Devices

10. 10
 Voice
- Natural
- Quick
- Frameworks like Alexa/Lex, Google Speech API
Interaction Techniques

11. 11
 Gestures / Hand Tracking
How?
- Hand tracking
- Gloves
- Controller
Interaction Techniques

12. 12
 Gaze based
Triggers
- blinking
- pressing a button
- staring
- gestures
Interaction Techniques

13. 13
 Gaming
 Movies
 Sales / Presentations
 Visualization
 Manuals
 Psychology
Applications

14. 14
 Car Showroom
 Lego AR
Applications @NTT Enso

15. 15
 Unity, Unreal Engine
 C#
 3D Models
 Drag-And-Drop
 Code snippets
Development

16. 16
 Motion sickness
 Guidance
 Drawing Attention
Problems

17. 17
Questions

18. 2 Application Scenario: Smart Factory

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Smart Factory
 Virtual + Real World
 Human workers
 Observation
 Data-analysis
 Root-cause-analysis

20. 20
 Best way through factory
 Workloads
 Break-downs
Problem: Path finding

21. 21
 Piece of software that acts autonomously
 Interacts with environment
Agent Systems

22. 22
 Multi Agenten Systeme
 Agents that cooperatore
 Cooperative or self-optimizing strategy
Multi Agent Systems

23. 23
 Simulation by Thomy Phan
(LMU)
 Agents work cooperatively
 Info like tasks, observations,
moving history,...
 Exchange infos with neighbors
 Reinforcement Learning
Problem: Path finding

24. 24
 Symptoms: Visible results of a
problem
 Problem: Gap between reality and
goal
 Roots: Invisible cause of a
problem
Root Cause Analysis

25. 25
 Algorithms can detect errors or outliers
 BUT:
 Only pre-trained anomalies (Distributions, Patterns,…)
 Computers are not creative
 Extend algorithmic analysis with visual approach (VR)
Algorithmic vs. Visual Analysis

26. 26
 Humans can detect patterns visually
 Enable creative approach
 Enable discussion
Algorithmic vs. Visual Analysis

27. 27
Short overview
Daten: ((X,Y,T),…)

28. 28
 Teleport
 Camera positions
 View item processing stage
 View item detail information
 View item paths
 Heatmap
 Time travel
Features

29. 29
Controller Interaction
Right Controller
 Pad (Teleport)
Left Controller:
 LaserPointer
 Trigger
 MenuButton
 Pad
Features
Alexa „Ask Evade to…“
 „… switch camera“
 „... pause“
 „… resume“
 „… reset“
 „… toggle Heatmap“
 „… show Itemdetails of…“
 „… Jump to timestep“
 „… Show item menu“