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07/04/2023
Physics-based Motion Retargeting from Sparse Inputs
Avatars are important to create interactive and immersive experiences in...
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06/15/2023
Hierarchical Planning and Control for Box Loco-Manipulation
Humans perform everyday tasks using a combination of locomotion and mani...
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10/24/2022
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
Policies produced by deep reinforcement learning are typically character...
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10/03/2022
OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviors
Reinforcement Learning (RL) has seen many recent successes for quadruped...
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05/08/2022
Learning to Brachiate via Simplified Model Imitation
Brachiation is the primary form of locomotion for gibbons and siamangs, ...
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04/11/2022
Evaluating Vision Transformer Methods for Deep Reinforcement Learning from Pixels
Vision Transformers (ViT) have recently demonstrated the significant pot...
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03/07/2022
A Survey on Reinforcement Learning Methods in Character Animation
Reinforcement Learning is an area of Machine Learning focused on how age...
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03/04/2022
Style-ERD: Responsive and Coherent Online Motion Style Transfer
Motion style transfer is a common method for enriching character animati...
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02/06/2022
Exploration with Multi-Sample Target Values for Distributional Reinforcement Learning
Distributional reinforcement learning (RL) aims to learn a value-network...
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10/28/2021
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence
Machine learning has long since become a keystone technology, accelerati...
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05/02/2021
Discovering Diverse Athletic Jumping Strategies
We present a framework that enables the discovery of diverse and natural...
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04/20/2021
GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model
Model-free reinforcement learning (RL) for legged locomotion commonly re...
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03/26/2021
Character Controllers Using Motion VAEs
A fundamental problem in computer animation is that of realizing purpose...
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11/04/2020
Dynamics Randomization Revisited:A Case Study for Quadrupedal Locomotion
Understanding the gap between simulation andreality is critical for rein...
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10/09/2020
Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning
Learning to locomote is one of the most common tasks in physics-based an...
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09/22/2020
Learning Task-Agnostic Action Spaces for Movement Optimization
We propose a novel method for exploring the dynamics of physically based...
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05/09/2020
ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills
Humans are highly adept at walking in environments with foot placement c...
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12/06/2019
Learning to Correspond Dynamical Systems
Correspondence across dynamical systems can lend us better tools for lea...
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03/22/2019
Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie
Deep reinforcement learning (DRL) is a promising approach for developing...
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04/17/2018
Terrain RL Simulator
We provide 89 challenging simulation environments that range in difficul...
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04/08/2018
DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
A longstanding goal in character animation is to combine data-driven spe...
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03/15/2018
Feedback Control For Cassie With Deep Reinforcement Learning
Bipedal locomotion skills are challenging to develop. Control strategies...
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02/13/2018
Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control
Deep reinforcement learning has demonstrated increasing capabilities for...
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01/11/2018
Model-Based Action Exploration
Deep reinforcement learning has great stride in solving challenging moti...
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11/03/2016