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This research introduces Belief-Overlap Partial Inversion (BOPI), a novel algorithm enabling humanoids to dynamically replan locomotion and manipulation tasks when interacting with objects of unknown dynamics. By mathematically balancing the disruption caused by belief updates against the risk of straying from proven paths, the method significantly reduces positioning errors in both simulation and hardware experiments. It represents a meaningful advancement in online estimation and flow-based planning for embodied AI agents operating in uncertain environments.
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Belief-Overlap Partial Inversion: Object-Centric Flow Replanning for Humanoid Loco-Manipulation

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2610.13087v1 Announce Type: new Abstract: People often learn how an unfamiliar object moves through a small exploratory push, using its response to guide their next motion. Inspired by this behavior, we study humanoids pushing carts whose mass and caster stiffness are initially unknown. Our object-centric framework closes online estimation, flow-based planning, and whole-body control into a loop, creating a tension: replacing the plan whenever the belief shifts disrupts the maneuver under way, while keeping it strands the robot on a path its evidence has ruled out. Belief-Overlap Partial Inversion (BOPI) scales revision to agreement, inverting the flow under the old belief only as far as the beliefs disagree before reconstructing under the new one. Across 18 simulated goals it lowers pooled final position and yaw error by roughly 33% and 47% against fixed-depth replanning, and on hardware it translates and turns a non-holonomic cart.

Abstract:People often learn how an unfamiliar object moves through a small exploratory push, using its response to guide their next motion. Inspired by this behavior, we study humanoids pushing carts whose mass and caster stiffness are initially unknown. Our object-centric framework closes online estimation, flow-based planning, and whole-body control into a loop, creating a tension: replacing the plan whenever the belief shifts disrupts the maneuver under way, while keeping it strands the robot on a path its evidence has ruled out. Belief-Overlap Partial Inversion (BOPI) scales revision to agreement, inverting the flow under the old belief only as far as the beliefs disagree before reconstructing under the new one. Across 18 simulated goals it lowers pooled final position and yaw error by roughly 33% and 47% against fixed-depth replanning, and on hardware it translates and turns a non-holonomic cart.

Robotics (cs.RO)

arXiv:2610.13087 [cs.RO]

(or arXiv:2610.13087v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2610.13087 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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