title: Hierarchical Visuomotor Control of Humanoids
abstract: 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. Supplementary video link:  https://youtu.be/fBoir7PNxPk
authors: Josh Merel Arun Ahuja Vu Pham Saran Tunyasuvunakool Siqi Liu Dhruva Tirumala Nicolas Heess Greg Wayne
hIndex: Nicolas Heess 47