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Erstellt / Aktualisiert 21.06.2020 / 25.10.2020
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Robot Safety Standards. 
There are 3 Standards. Name them

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A-Level: Functional Safety (IEC 61508) / Assesement (ISO 12100 - Risk)


B-Level: EN ISO / IEC


C-Level: Integrated manufacturing systems / Robot System, cell / Robot

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EU Definition of Artificial Intelligence

sense - think (plan) - act

Machine Learning 

  • (Deep Learning, Reinforced Learning)
  • Reasoning - information processiong (Search, Planning, Knowledge) - Decision making
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Research fields of diferent at Pichelrs institute: 

  • Object Detection 
  • Sematic Scene Segmentation 
  • Human Pose Detection
  • Deep Reinforcement Learning
  • Object Detection (3D needed for Robotics, Video mit Hund und Rad)
  • Sematic Scene Segmentation (autonomous driving, what is the scene about? Meaning)
  • Human Pose Detection (Video mit Sportlern, Tänzern) Auch hier 2D schon relativ gut, 3D noch nicht
  • Deep Reinforcement Learning (Robots learning to move)
  • Online Training (Robot learns objects, Robot dealing with unknown situations or objects)
  • Learning Robot Grasping Policies (Greifarme, Objekte greifen)
  • Imitation learning (Video mit Glas füllen)
  • Deep Reinforcement learning (sorting out a bin, make space to grab and place things)


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What is trust?
What is a trustfull person?

Cambridge Dictionary: 
Trust is to believe that someone is good and honest and will not harm you, or that something is safe and reliable

Trustful person: 

  • Consistency and reliabilty (meet the expectations, avoid surprises and risks
  • Adequacy and adaptability
  • execution (always competent and professional)
  • Honesty and openness (communicate inform and explain; point to room for imporovement)




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Trustworthy Robots: Safety, Creditibility and Explainability

EU guidelines for Turstworthy AI published april 8, 2019: What does this document?


  • it talks about requirements of trustworthy Ai
  • Technical methods when realising explainable AI
  • Also if you have a system how to assess that it is trustworthy
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Framework for Trustworthy AI

Introduction (3)
Chapter 1 (2)
Chapter 2
Chapter 3

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Introduction: Lawfull Ai, Ethical Ai, Robust AI

Chapter 1: Foundations of Trustworthy AI -> 4 Ethical Principles (Respect for human autonomy, Prevention of harm, frames, Explicability)


Chapter 2: Realisation or Trustworthy AI -> 7 key Requierements (Technical, non technical methods) 
1. Human agency and oversight
2. Technical robustness and safety
3. Privacy and data governance
4. Transparancy
5. Diversity, non-discrimination and fairness
6. Societal and environmental wellbeing
7. accountability

Chapter 3: Assesment of Trustworthy AI -> Trustworthy AI Assesement List


7 key requierements of trustworthy Ai

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Again: 7 Keyrequirements of Trustworthy AI: 

  1. Human agency and oversight
  2. Technical Robustness and safety
  3. Privacy and Data governance
  4. Transparency
  5. Diversity, non-discrimination and fairness
  6. Societal and environmental wellbeing
  7. Accountability (Auditability and accounting)
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Technical Methods for Trustworthy AI (5)

  1. Archticures for Trustworthy Ai
  2. Ethics and rule of law by design
  3. Explanation methods (X to AI)
  4. Testing and validating 
  5. Quality of Service Indicators