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Terrain Runner: Control, Parameterization, Composition, and Planning for Highly Dynamic Motions
| Content Provider | CiteSeerX |
|---|---|
| Author | Yin, Kangkang Panne, Michiel Liu, Libin Guo, Baining |
| Abstract | Figure 1: An animated character runs, vaults, jumps, and drop-rolls across a parkour terrain during a real-time physics-based simulation. Given a single motion capture clip of each of these four skills as input, our method uses an offline process to develop robust control policies for parameterized versions of these skills, as well as robust transition motions. In this paper we learn the skills required by real-time physics-based avatars to perform parkour-style fast terrain crossing using a mix of running, jumping, speed-vaulting, and drop-rolling. We begin with a single motion capture example of each skill and then learn reduced-order linear feedback control laws that provide robust execution of the motions during forward dynamic simulation. We then parameterize each skill with respect to the environment, such as the height of obstacles, or with respect to the task parameters, such as running speed and direction. We employ a continuation process to achieve the required parameterization of the motions and their affine feedback laws. The continuation method uses a predictor-corrector method based on radial basis functions. Lastly, we build control laws specific to the sequential composition of different skills, so that the simulated character can robustly transition to obstacle clearing maneuvers from running whenever obstacles are encountered. The learned transition skills work in tandem with a simple online step-based planning algorithm, and together they robustly guide the character to achieve a state that is well-suited for the chosen obstacle-clearing motion. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Real-time Physics-based Avatar Robust Execution Reduced-order Linear Feedback Control Law Predictor-corrector Method Single Motion Capture Clip Real-time Physics-based Simulation Terrain Runner Learned Transition Skill Highly Dynamic Motion Robust Transition Motion Radial Basis Function Parkour-style Fast Terrain Parkour Terrain Simulated Character Sequential Composition Animated Character Run Task Parameter Continuation Method Single Motion Capture Example Robust Control Policy Simple Online Step-based Planning Algorithm Affine Feedback Law Forward Dynamic Simulation Offline Process Required Parameterization Different Skill Chosen Obstacle-clearing Motion Parameterized Version Continuation Process |
| Content Type | Text |
| Resource Type | Article |
