Galbot Introduces PASSAGE Framework for Humanoid Robot Travel
Overview
Galbot's PASSAGE framework enables humanoid robots to navigate complex environments with 98.67% success on a benchmark, using human data and reactive motion planning. It combines obstacle stepping and fall response for human-like locomotion.
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Reported quantity · Reported duration: 100 hours · Basis not reported
“Built on 100 hours of human data across 1,500 scenes, it achieves 98.67% success on the Clutter Scene Traversal benchmark.”
Exact source · revision 1chris-paxton
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- Chris Paxton — X RoboticsCombining obstacle stepping with fall response to create reactive human-like robots
The Galbot team introduces PASSAGE, a framework that integrates environmental perception, whole-body motion planning, and closed-loop control to enable humanoid robots to autonomously navigate complex environments. Trained on 100 hours of human data across 1,500 scenes, it achieves 98.67% success on the Clutter Scene Traversal benchmark, showcasing advancements in reactive human-like locomotion.
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