Hierarchical reinforcement learning: A comprehensive survey
Hierarchical Reinforcement Learning (HRL) enables autonomous decomposition of
challenging long-horizon decision-making tasks into simpler subtasks. During the past …
challenging long-horizon decision-making tasks into simpler subtasks. During the past …
Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation
Modeling human motor control and predicting how humans will move in novel environments
is a grand scientific challenge. Researchers in the fields of biomechanics and motor control …
is a grand scientific challenge. Researchers in the fields of biomechanics and motor control …
Diffusion-based generation, optimization, and planning in 3d scenes
We introduce SceneDiffuser, a conditional generative model for 3D scene understanding.
SceneDiffuser provides a unified model for solving scene-conditioned generation …
SceneDiffuser provides a unified model for solving scene-conditioned generation …
Legged locomotion in challenging terrains using egocentric vision
Animals are capable of precise and agile locomotion using vision. Replicating this ability
has been a long-standing goal in robotics. The traditional approach has been to decompose …
has been a long-standing goal in robotics. The traditional approach has been to decompose …
Learning robust perceptive locomotion for quadrupedal robots in the wild
Legged robots that can operate autonomously in remote and hazardous environments will
greatly increase opportunities for exploration into underexplored areas. Exteroceptive …
greatly increase opportunities for exploration into underexplored areas. Exteroceptive …
Amp: Adversarial motion priors for stylized physics-based character control
Synthesizing graceful and life-like behaviors for physically simulated characters has been a
fundamental challenge in computer animation. Data-driven methods that leverage motion …
fundamental challenge in computer animation. Data-driven methods that leverage motion …
Extreme parkour with legged robots
Humans can perform parkour by traversing obstacles in a highly dynamic fashion requiring
precise eye-muscle coordination and movement. Getting robots to do the same task requires …
precise eye-muscle coordination and movement. Getting robots to do the same task requires …
Learning agile robotic locomotion skills by imitating animals
Reproducing the diverse and agile locomotion skills of animals has been a longstanding
challenge in robotics. While manually-designed controllers have been able to emulate many …
challenge in robotics. While manually-designed controllers have been able to emulate many …
Deepphase: Periodic autoencoders for learning motion phase manifolds
Learning the spatial-temporal structure of body movements is a fundamental problem for
character motion synthesis. In this work, we propose a novel neural network architecture …
character motion synthesis. In this work, we propose a novel neural network architecture …