aiqbench analysis
This paper addresses motion retargeting for humanoid robots by introducing a prioritized framework that enforces strict hierarchies over conflicting optimization objectives. By ensuring critical constraints like foot placement and object contacts take precedence, the method generates more reliable reference trajectories for complex interactions involving multiple agents. This advancement directly improves the preprocessing pipeline essential for deploying autonomous humanoid systems in dynamic environments.
PriMoRetarget: Humanoid Motion Transfer Through Prioritized Motion Retargeting
arXiv:2610.12642v1 Announce Type: new Abstract: Motion retargeting is a critical preprocessing step for transferring human motion data to humanoid robots. While existing methods are effective for single-character motions, interactions involving multiple characters and objects introduce additional contacts and spatial relationships that must be preserved. Retargeting is commonly formulated as a weighted multi-objective optimization problem, where conflicting objectives can require careful tuning of relative weights and can still compromise important motion characteristics. We introduce PriMoRetarget, a prioritized motion-retargeting framework that replaces relative objective weighting with an explicit priority hierarchy. Lower-priority updates are constrained to preserve higher-priority objectives, allowing critical characteristics such as foot placement and interaction contacts to take precedence over lower-priority pose objectives. The method is evaluated on four datasets spanning single-character motion, character-object manipulation, and character-character interactions. The resulting motions better preserve task-relevant interactions and provide reference trajectories that can be tracked more reliably than those produced by widely used retargeting methods.
Abstract:Motion retargeting is a critical preprocessing step for transferring human motion data to humanoid robots. While existing methods are effective for single-character motions, interactions involving multiple characters and objects introduce additional contacts and spatial relationships that must be preserved. Retargeting is commonly formulated as a weighted multi-objective optimization problem, where conflicting objectives can require careful tuning of relative weights and can still compromise important motion characteristics. We introduce PriMoRetarget, a prioritized motion-retargeting framework that replaces relative objective weighting with an explicit priority hierarchy. Lower-priority updates are constrained to preserve higher-priority objectives, allowing critical characteristics such as foot placement and interaction contacts to take precedence over lower-priority pose objectives. The method is evaluated on four datasets spanning single-character motion, character-object manipulation, and character-character interactions. The resulting motions better preserve task-relevant interactions and provide reference trajectories that can be tracked more reliably than those produced by widely used retargeting methods.
Robotics (cs.RO); Graphics (cs.GR)
arXiv:2610.12642 [cs.RO]
(or arXiv:2610.12642v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2610.12642 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 243 words
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