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Generating Upper-Body Motion for Real-Time Characters Making their Way through Dynamic Environments
Neural method generating reactive upper-body secondary motion for locomoting characters navigating dynamic obstacles in real time.
Abstract
Real‐time character animation in dynamic environments requires the generation of plausible upper‐body movements regardless of the nature of the environment, including non‐rigid obstacles such as vegetation. We propose a flexible model for upper‐body interactions, based on the anticipation of the character's surroundings, and on antagonistic controllers to adapt the amount of muscular stiffness and response time to better deal with obstacles. Our solution relies on a hybrid method for character animation that couples a keyframe sequence with kinematic constraints and lightweight physics. The dynamic response of the character's upper‐limbs leverages antagonistic controllers, allowing us to tune tension/relaxation in the upper‐body without diverging from the reference keyframe motion. A new sight model, controlled by procedural rules, enables high‐level authoring of the way the character generates interactions by adapting its stiffness and reaction time. As results show, our real‐time method offers precise and explicit control over the character's behavior and style, while seamlessly adapting to new situations. Our model is therefore well suited for gaming applications.
How to read this
- Category
- Method: real-time reactive upper-body motion for characters in dynamic environments
- Contributions
- A flexible upper-body interaction model based on anticipating the character's surroundings, including non-rigid obstacles such as vegetation
- Antagonistic controllers that tune muscular stiffness and response time to adapt to obstacles without diverging from a reference keyframe motion
- A procedurally controlled sight model enabling high-level authoring of interaction style, stiffness, and reaction time
- Context
- A hybrid keyframe-plus-lightweight-physics approach to secondary character motion for games, relating to data-driven locomotion such as Clavet's Motion Matching and the Road to Next-Gen Animation.Builds on: Motion Matching and The Road to Next-Gen Animation
- Correctness
- Couples a keyframe sequence with kinematic constraints and lightweight physics, so plausibility rather than physical exactness is the goal; the antagonistic-controller and sight-model design are validated by demonstration and aimed at gaming, so behavior under extreme or unanticipated environments is the caveat.
- Clarity
- Accessible; a first pass conveys the anticipation-plus-antagonistic-controller idea without heavy math.
- How to read it
- First pass for how anticipation, stiffness control, and the sight model combine for reactive motion; a second pass for the controller formulation if you want to author or tune the behavior in a real-time system.
Builds on
Built upon by
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Related work
- Joint-Dependent Local Deformations for Hand Animation and Object Grasping 1988 / SIGGRAPH
- Rig-Space Physics 2012 / SIGGRAPH
- SKEL-Betweener: a Neural Motion Rig for Interactive Motion Authoring 2024 / SIGGRAPH Asia
- Dog Code: Human to Quadruped Embodiment Using Shared Codebooks 2024 / MIG
Keywords
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