#terrain-adaptation News & Analysis

2 articles tagged with #terrain-adaptation. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 47/10

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CoRe-MoE: Contrastive Reweighted Mixture of Experts for Multi-Terrain Humanoid Locomotion with Gait Adaptation

Researchers introduce CoRe-MoE, a reinforcement learning framework enabling humanoid robots to seamlessly transition between walking and running while adapting to complex terrains. The two-stage approach decouples gait generation from terrain adaptation using a contrastive learning mechanism, with successful zero-shot deployment on a Unitree G1 robot across varied outdoor environments.

AINeutralarXiv – CS AI · Jun 196/10

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CTS-MoE: Implicit Terrain Adaptation via Mixture-of-Experts for Perceptive Locomotion

Researchers introduce CTS-MoE, a machine learning approach that enables legged robots to traverse complex terrain by dynamically adapting their locomotion strategy through a mixture-of-experts architecture guided by perception. Tested on the Unitree Go1 robot, the system outperforms traditional monolithic policies in handling stairs, gaps, and obstacles without requiring explicit terrain classification.