Show simple item record

dc.contributor.authorXie, Zhaomingen_US
dc.contributor.authorLing, Hung Yuen_US
dc.contributor.authorKim, Nam Heeen_US
dc.contributor.authorPanne, Michiel van deen_US
dc.contributor.editorBender, Jan and Popa, Tiberiuen_US
dc.description.abstractHumans are highly adept at walking in environments with foot placement constraints, including stepping-stone scenarios where footstep locations are fully constrained. Finding good solutions to stepping-stone locomotion is a longstanding and fundamental challenge for animation and robotics. We present fully learned solutions to this difficult problem using reinforcement learning. We demonstrate the importance of a curriculum for efficient learning and evaluate four possible curriculum choices compared to a non-curriculum baseline. Results are presented for a simulated humanoid, a realistic bipedal robot simulation and a monster character, in each case producing robust, plausible motions for challenging stepping stone sequences and terrains.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectReinforcement learning
dc.subjectPhysical simulation
dc.titleALLSTEPS: Curriculum-driven Learning of Stepping Stone Skillsen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersCharacter Animation 1

Files in this item


This item appears in the following Collection(s)

  • 39-Issue 8
    ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2020

Show simple item record