Interactive Design of Stylized Walking Gaits for Robotic Characters
Michael A. Hopkins, Georg Wiedebach, Kyle Cesare, Jared Bishop, Espen Knoop, Moritz Bächer
Abstract
Procedural animation has seen widespread use in the design of expressive walking gaits for virtual characters. While similar tools could breathe life into robotic characters, existing techniques are largely unaware of the kinematic and dynamic constraints imposed by physical robots. In this paper, we propose a system for the artist-directed authoring of stylized bipedal walking gaits, tailored for execution on robotic characters. The artist interfaces with an interactive editing tool that generates the desired character motion in realtime, either on the physical or simulated robot, using a model-based control stack. Each walking style is encoded as a set of sample parameters which are translated into whole-body reference trajectories using the proposed procedural animation technique. In order to generalize the stylized gait over a continuous range of input velocities, we employ a phase-space blending strategy that interpolates a set of example walk cycles authored by the animator while preserving contact constraints. To demonstrate the utility of our approach, we animate gaits for a custom, free-walking robotic character, and show, with two additional in-simulation examples, how our procedural animation technique generalizes to bipeds with different degrees of freedom, proportions, and mass distributions.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext ca58f529-85c9-497d-94f7-9fcac69049c6Cited by top-tier papers1
Ask how each one uses itBuilds on3
- ASE: large-scale reusable adversarial skill embeddings for physically simulated charactersXue Bin Peng, Yunrong Guo, Lina Halper, Sergey Levine et al.SIGGRAPH 2022 · 217 citations
- Physics-based character controllers using conditional VAEsJungdam Won, Deepak Gopinath, Jessica K. HodginsSIGGRAPH 2022 · 95 citations
- Learning a family of motor skills from a single motion clipSeyoung Lee, Sunmin Lee, Yongwoo Lee, Jehee LeeSIGGRAPH 2021 · 35 citations
Related papers
- Designing actuation systems for animatronic figures via globally optimal discrete searchSimon Huber, Roi Poranne, Stelian CorosSIGGRAPH 2021 · 4 citations
- A Layered Authoring Tool for Stylized 3D animationsJiaju Ma, Li-Yi Wei, Rubaiat Habib KaziCHI 2022 · 22 citations
- Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory DiffusionDavis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan et al.CVPR 2023
- ViSA: Physics-based Virtual Stunt Actors for Ballistic StuntsMinseok Kim, Wonjeong Seo, Sung-Hee Lee, Jungdam WonSIGGRAPH 2025 · 1 citation
- Taming Diffusion Probabilistic Models for Character ControlRui Chen, Mingyi Shi, Shaoli Huang, Ping Tan et al.SIGGRAPH 2024 · 30 citations
