CyberDemo: Augmenting Simulated Human Demonstration for Real-World
  Dexterous Manipulation
We introduce CyberDemo, a novel approach to robotic imitation learning that
leverages simulated human demonstrations for real-world tasks. By incorporating
extensive data augmentation in a simulated environment, CyberDemo outperforms
traditional in-domain real-world demonstrations when transferred to the real
world, handling diverse physical and visual conditions. Regardless of its
affordability and convenience in data collection, CyberDemo outperforms
baseline methods in terms of success rates across various tasks and exhibits
generalizability with previously unseen objects. For example, it can rotate
novel tetra-valve and penta-valve, despite human demonstrations only involving
tri-valves. Our research demonstrates the significant potential of simulated
human demonstrations for real-world dexterous manipulation tasks. More details
can be found at https://cyber-demo.github.io
65d82591a5269668b716fcfa
Jun Wang
65d82591a5269668b716fcfb
Yuzhe Qin
admin_assigned
2024-02-23T13:13:06.224Z
64ad64c2c1da7c4dbc7b19c5
/avatars/98efbab6c65405e8701c64c290a7a87c.svg
Yuzhe Qin
user
yuzheqin
65d82591a5269668b716fcfc
Kaiming Kuang
65d82591a5269668b716fcfd
Yigit Korkmaz
claimed_verified
2024-02-24T14:37:02.812Z
65d8e45d0884c37e111d5ee0
/avatars/989d9d6caf0f6adb4c8297125a0b86ad.svg
Yigit Korkmaz
user
ykorkmaz
65d82591a5269668b716fcfe
Akhilan Gurumoorthy
65d82591a5269668b716fcff
Hao Su
65d82591a5269668b716fd00
Xiaolong Wang
CyberDemo: Augmenting Simulated Human Demonstration for Real-World
  Dexterous Manipulation
We introduce CyberDemo, a novel approach to robotic imitation learning that
leverages simulated human demonstrations for real-world tasks. By incorporating
extensive data augmentation in a simulated environment, CyberDemo outperforms
traditional in-domain real-world demonstrations when transferred to the real
world, handling diverse physical and visual conditions. Regardless of its
affordability and convenience in data collection, CyberDemo outperforms
baseline methods in terms of success rates across various tasks and exhibits
generalizability with previously unseen objects. For example, it can rotate
novel tetra-valve and penta-valve, despite human demonstrations only involving
tri-valves. Our research demonstrates the significant potential of simulated
human demonstrations for real-world dexterous manipulation tasks. More details
can be found at https://cyber-demo.github.io
CyberDemo leverages augmented simulated human demonstrations to enhance real-world robotic imitation learning, improving success rates and generalizability across diverse tasks and objects.
robotic imitation learning simulated human demonstrations data augmentation generalizability dexterous manipulation tasks