Hierarchical visuomotor control of humanoids
Merel, Josh, Ahuja, Arun, Pham, Vu, Tunyasuvunakool, Saran, Liu, Siqi, Tirumala, Dhruva, Heess, Nicolas, Wayne, Greg
–arXiv.org Artificial Intelligence
We aim to build complex humanoid agents that integrate perception, motor control, and memory. In this work, we partly factor this problem into low-level motor control from proprioception and high-level coordination of the low-level skills informed by vision. We develop an architecture capable of surprisingly flexible, task-directed motor control of a relatively high-DoF humanoid body by combining pre-training of low-level motor controllers with a high-level, task-focused controller that switches among low-level sub-policies. The resulting system is able to control a physically-simulated humanoid body to solve tasks that require coupling visual perception from an unstabilized egocentric RGB camera during locomotion in the environment. For a supplementary video link, see https://youtu.be/7GISvfbykLE .
arXiv.org Artificial Intelligence
Nov-23-2018
- Country:
- North America > United States (0.14)
- Genre:
- Research Report (0.82)
- Technology:
- Information Technology > Artificial Intelligence
- Cognitive Science (1.00)
- Machine Learning
- Neural Networks > Deep Learning (0.31)
- Reinforcement Learning (0.95)
- Representation & Reasoning (0.93)
- Robots (0.94)
- Information Technology > Artificial Intelligence