
AI for Manipulation Paper Presentation
Authored by Alexis Sudjianto
Mathematics
University
Used 3+ times

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7 questions
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1.
OPEN ENDED QUESTION
3 mins • 1 pt
How would you describe dexterous manipulation?
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2.
OPEN ENDED QUESTION
3 mins • 1 pt
What are some things that you found interesting about either of the papers?
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3.
MULTIPLE SELECT QUESTION
45 sec • 1 pt
How are the two approaches to learning dexterous manipulation similar? (Select all that apply)
Both approaches use the Shadow Dexterous Hand
They both use point clouds in order to map the environment
Both approaches conduct simulations for training
The goal of both approaches was to better generalize to novel goals
4.
MULTIPLE SELECT QUESTION
30 sec • 1 pt
How do the two approaches differ? (Select all that apply)
DexDeform uses human demonstration
OpenAI uses reinforcement learning, DexForm doesn't
DexDeform deals with deformable objects, OpenAI doesn't
DexDeform uses reinforcement learning, OpenAI doesn't
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What are the three steps of the DexDeform?
1. learning from videos, 2. skill abstraction, 3. exploration with novel goals
1. learning from manually moving the robot, 2. skill abstraction, 3. exploration with novel goals
1. learning via teleoperation, 2. manually labeling the actions, 3. exploration with novel goals
1. learning via teleoperation, 2. skill abstraction, 3. exploration with novel goals
6.
FILL IN THE BLANK QUESTION
1 min • 1 pt
In the OpenAI paper, the policy is trained with Proximal Policy Optimization (PPO), which requires a policy network and a _____ network
7.
OPEN ENDED QUESTION
3 mins • 1 pt
Do you have any questions about the paper that our presentation didn't cover?
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