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Conditioning robot policies on a spatiotemporal feature map enables faster and more robust long-horizon mobile manipulation, outperforming traditional image-only approaches.
Achieve 3x faster convergence in distributed multi-robot pose graph optimization by strategically sharing just 36Kb of pose data between robots per iteration.
