J-LAW introduces a coupled latent factor graph that jointly optimizes metric poses, latent states, and landmark embeddings to produce maps that are both metric and actionable for planning.
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A three-stage offline SDRE-based controller uses motion-capture data to achieve high-fidelity human motion reproduction on a suspended bipedal robot with average RMSE below 3 degrees for squatting and walking tasks.
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J-LAW: Joint Localization and Actionable World Modeling via Coupled Latent Factor Graphs
J-LAW introduces a coupled latent factor graph that jointly optimizes metric poses, latent states, and landmark embeddings to produce maps that are both metric and actionable for planning.
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A Three-Stage Offline SDRE-Based Control Framework for Human Motion Reproduction on a Suspended Bipedal Robot
A three-stage offline SDRE-based controller uses motion-capture data to achieve high-fidelity human motion reproduction on a suspended bipedal robot with average RMSE below 3 degrees for squatting and walking tasks.