TY  - JOUR
TI  - DOC: Differentiable Optimal Control for Retargeting Motions onto Legged Robots
AU  - Grandia, R.
AU  - Farshidian, F.
AU  - Knoop, E.
AU  - Schumacher, C.
AU  - Hutter, M.
AU  - Bacher, M.
PY  - 2023
DA  - 2023/07//
JO  - ACM Transactions on Graphics (SIGGRAPH 2023)
AB  - DOC, by Grandia, Farshidian, Knoop, Schumacher, Hutter and Bacher from Disney Research and ETH Zurich, presents a differentiable optimal control framework for retargeting authored or motion-captured animation onto physically simulated legged robots. The work received a Best Paper award at SIGGRAPH 2023. Its primary nexus is robotic-character performance, with animation-education relevance as the bridge between digital animation authoring and the physical execution of character motion -- a connection of increasing practical importance as animatronic and robotic characters enter theme-park and performance contexts.
KW  - motion-synthesis
KW  - character-animation
UR  - https://dl.acm.org/doi/10.1145/3592454
LA  - en
ER  -