Light-Loco-Parkour: legged robot picks vault or climb on its own using only onboard sensing
chris_j_paxton · x · 2026-09-16
Light Origins unveiled Light-Loco-Parkour: a legged-robot policy that decides on the fly when to walk, vault, climb or traverse complex terrain — with no human commands or sub-task labels.
- Relies entirely on onboard sensing, selecting locomotion skills in real time as it moves.
- Unlike approaches built on large motion corpora, it learns from sparse seeds, needing no per-skill sub-task annotation.
- The team, including Xiaodao Chen, Yuntao, Micool Cho and Chris Paxton, details the method on RoboPapers Episode 104.
Related event: Light Origins Shows Humanoid Robots Zero-Shot Parkour on Rough Terrain(3 posts)→
More from Embodied
- Physical AI's real story: a 4-layer map of 15 companies behind humanoid robots — pdamodaran · 2026-11-02
- Autonomous's Harness Pro uses an ESP32-P4, not a mini PC, to monitor AI coding agents — dee_hw · 2026-11-02
- KAIST's QCP lets robot policies control execution quality in real time — kaist-ai · 2026-11-02
- ANYbotics begins customer deliveries of ANYmal X, first legged robot certified for explosive atmospheres — lukas_m_ziegler · 2026-11-02
- InSpatio opens China's first embodied simulation data center targeting 1M hours/month — 智东西 · 2026-11-02
- GR-BC mines better trajectories from imperfect demos, hitting ~91% success on precise manipulation — 机器之心 · 2026-11-02