Feedback in Robotics

Jonas discusses the challenges of automating fringe cases in industrial applications and emphasizes the importance of real-time feedback for robotic manipulation. He highlights how human motion, though imprecise, excels at adjusting based on feedback, a skill that current industrial robots lack. By leveraging advancements in machine learning and computer vision, he aims to enable robots to react dynamically to their environment, improving their interaction with objects.

In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Robotics at OpenAI with Jonas Schneider - #76
Related Questions
- How is machine learning used in robots?
- Is the interaction of robots in the physical world a signal that could be used in reinforcement learning as discussed in the episode Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10 and the clip Teaching Robots Skills?

Feedback in Robotics

In this clip

From this podcast

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Robotics at OpenAI with Jonas Schneider - #76

Related Questions

How is machine learning used in robots?

Is the interaction of robots in the physical world a signal that could be used in reinforcement learning as discussed in the episode Pieter Abbeel: Deep Reinforcement Learning | Lex Fridman Podcast #10 and the clip Teaching Robots Skills?