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Learning to Brachiate via Simplified Model Imitation


May 08, 2022
Daniele Reda, Hung Yu Ling, Michiel van de Panne

* 11 pages, 6 figures. Accepted at SIGGRAPH 2022. For videos, supplementary material and code, visit the following URL https://brachiation-rl.github.io/brachiation 

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Learning to Get Up


Apr 30, 2022
Tianxin Tao, Matthew Wilson, Ruiyu Gou, Michiel van de Panne


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Evaluating Vision Transformer Methods for Deep Reinforcement Learning from Pixels


Apr 11, 2022
Tianxin Tao, Daniele Reda, Michiel van de Panne


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Style-ERD: Responsive and Coherent Online Motion Style Transfer


Mar 29, 2022
Tianxin Tao, Xiaohang Zhan, Zhongquan Chen, Michiel van de Panne

* CVPR 2022, project page: https://tianxintao.github.io/Online-Motion-Style-Transfer 

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A Survey on Reinforcement Learning Methods in Character Animation


Mar 07, 2022
Ariel Kwiatkowski, Eduardo Alvarado, Vicky Kalogeiton, C. Karen Liu, Julien Pettré, Michiel van de Panne, Marie-Paule Cani

* 27 pages, 6 figures, Eurographics STAR, Computer Graphics Forum 

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Exploration with Multi-Sample Target Values for Distributional Reinforcement Learning


Feb 06, 2022
Michael Teng, Michiel van de Panne, Frank Wood

* Submitted to ICML 2022 

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Discovering Diverse Athletic Jumping Strategies


May 02, 2021
Zhiqi Yin, Zeshi Yang, Michiel van de Panne, KangKang Yin

* ACM Trans. Graph. 40, 4, Article 91 (August 2021), 17 pages (2021) 
* 17 pages; SIGGRAPH 2021 

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GLiDE: Generalizable Quadrupedal Locomotion in Diverse Environments with a Centroidal Model


Apr 22, 2021
Zhaoming Xie, Xingye Da, Buck Babich, Animesh Garg, Michiel van de Panne


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Character Controllers Using Motion VAEs


Mar 26, 2021
Hung Yu Ling, Fabio Zinno, George Cheng, Michiel van de Panne

* Project page: https://www.cs.ubc.ca/~hyuling/projects/mvae/ ; Code: https://github.com/electronicarts/character-motion-vaes 

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Dynamics Randomization Revisited:A Case Study for Quadrupedal Locomotion


Nov 04, 2020
Zhaoming Xie, Xingye Da, Michiel van de Panne, Buck Babich, Animesh Garg


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Learning to Locomote: Understanding How Environment Design Matters for Deep Reinforcement Learning


Oct 09, 2020
Daniele Reda, Tianxin Tao, Michiel van de Panne

* Presented at The 13th Annual ACM SIGGRAPH Conference on Motion, Interaction and Games 

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Learning Task-Agnostic Action Spaces for Movement Optimization


Sep 22, 2020
Amin Babadi, Michiel van de Panne, C. Karen Liu, Perttu Hämäläinen


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ALLSTEPS: Curriculum-driven Learning of Stepping Stone Skills


May 09, 2020
Zhaoming Xie, Hung Yu Ling, Nam Hee Kim, Michiel van de Panne


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Learning to Correspond Dynamical Systems


Dec 23, 2019
Nam Hee Kim, Zhaoming Xie, Michiel van de Panne


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Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie


Mar 22, 2019
Zhaoming Xie, Patrick Clary, Jeremy Dao, Pedro Morais, Jonathan Hurst, Michiel van de Panne


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Feedback Control For Cassie With Deep Reinforcement Learning


Jul 27, 2018
Zhaoming Xie, Glen Berseth, Patrick Clary, Jonathan Hurst, Michiel van de Panne

* 6 pages, 4 figures, accepted for IROS2018 

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DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills


Jul 27, 2018
Xue Bin Peng, Pieter Abbeel, Sergey Levine, Michiel van de Panne


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Terrain RL Simulator


Apr 17, 2018
Glen Berseth, Xue Bin Peng, Michiel van de Panne

* 10 pages 

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Model-Based Action Exploration for Learning Dynamic Motion Skills


Apr 12, 2018
Glen Berseth, Michiel van de Panne

* 7 pages, 7 figures, conference paper 

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Learning Locomotion Skills Using DeepRL: Does the Choice of Action Space Matter?


Nov 03, 2016
Xue Bin Peng, Michiel van de Panne


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