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    <title>humanoidintel.ai — Research</title>
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    <description>Research news and breakthroughs in humanoid robotics.</description>
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    <item>
      <title><![CDATA[Adaptive-MHE Closes Sim-to-Real Gap in Loco-Manipulation]]></title>
      <link>https://humanoidintel.ai/news/adaptive-mhe-sampling-mpc-loco-manipulation-mhe</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Adaptive-MHE couples online parameter estimation with sampling-based MPC to match ground-truth controller performance in legged loco-manipulation.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[Multi-Humanoid Cooperative Transport via Decentralized Control]]></title>
      <link>https://humanoidintel.ai/news/multi-humanoid-cooperative-transport-decentralized-object-centric-control</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Oregon State researchers demonstrate decentralized object-centric control enabling humanoid teams to cooperatively pick up and transport objects.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[RL Lifts VLA Accuracy from 42% to 97% in 10 Minutes]]></title>
      <link>https://humanoidintel.ai/news/real-time-expo-ft-rl-vla-fine-tuning</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Stanford researchers cut VLA latency-induced failure with RL, lifting task success from 42% to 97% in under 10 minutes of robot data.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[WholeBodyWAM Trains on 4K Hours of Human Motion]]></title>
      <link>https://humanoidintel.ai/news/wholebody-wam-world-action-model-motion-priors-2026</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[WholeBodyWAM uses 4K+ hours of heterogeneous human and humanoid motion to bootstrap whole-body manipulation without robot-specific labels.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[AdaDE Cuts VLA Parameters 40% With 95% Task Retention]]></title>
      <link>https://humanoidintel.ai/news/adade-dense-moe-vla-compression-2026</link>
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      <pubDate>Wed, 16 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[AdaDE converts VLA feed-forward blocks to MoE layers, deactivating 40% of LLM params while retaining 95.1% LIBERO success rate.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[RECAL Adds Collision Awareness to Blind WBCs on Digit V3]]></title>
      <link>https://humanoidintel.ai/news/recal-collision-aware-whole-body-control-digit-v3</link>
      <guid isPermaLink="true">https://humanoidintel.ai/news/recal-collision-aware-whole-body-control-digit-v3</guid>
      <pubDate>Wed, 16 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[RECAL wraps any blind WBC with a cross-attention layer that trades target tracking for collision safety on Digit V3.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[XRoboToolKit-T Adds Tactile Sensing to Teleoperation]]></title>
      <link>https://humanoidintel.ai/news/xrobotoolkit-t-tactile-teleoperation-contact-rich-manipulation</link>
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      <pubDate>Wed, 16 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[XRoboToolKit-T combines tactile force control and a VLA model to improve data collection for contact-rich manipulation tasks.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[GROOVE Cuts VLA Jerk 43% Without Retraining]]></title>
      <link>https://humanoidintel.ai/news/groove-geometry-guided-vla-jerk-reduction</link>
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      <pubDate>Tue, 15 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[GROOVE reduces rotational EEF jerk 43.42% on LIBERO with no retraining, boosting task success from 93.75% to 95.75%.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[REAL-I Challenge at ICRA 2026: VLA Training Lessons]]></title>
      <link>https://humanoidintel.ai/news/real-i-challenge-icra-2026-vla-training-lessons</link>
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      <pubDate>Tue, 15 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[ICRA 2026's REAL-I Challenge stress-tests VLA training on a shared dual-arm humanoid, exposing key limits of offline metrics.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[ShieldVLA Cuts Safety Violations 57% in VLA Models]]></title>
      <link>https://humanoidintel.ai/news/shieldvla-feasibility-aware-safety-alignment-vla-models</link>
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      <pubDate>Tue, 15 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[ShieldVLA uses HJ reachability to cut VLA safety violations 57% and boost task success +0.13 over SafeVLA.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[DATAFARM Closes the VLA Fine-Tuning Gap with TAMP]]></title>
      <link>https://humanoidintel.ai/news/datafarm-tamp-vla-fine-tuning-distribution-alignment</link>
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      <pubDate>Mon, 14 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[DATAFARM aligns TAMP trajectories with VLA pretraining distributions, hitting 56.7% vs 8.3% for raw TAMP.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[DWMP Uses Dual World Models for Humanoid Navigation]]></title>
      <link>https://humanoidintel.ai/news/dwmp-dual-world-models-humanoid-obstacle-traversal</link>
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      <pubDate>Mon, 14 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[DWMP splits proprioceptive and visual processing into separate world models, improving obstacle traversal on the Unitree G1.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[STAR Achieves 61% Success Rate on Dexterous Tasks]]></title>
      <link>https://humanoidintel.ai/news/star-sparse-tactile-representation-vtla-dexterous-manipulation</link>
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      <pubDate>Mon, 14 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[STAR framework hits 61% success rate on real-world dexterous tasks using a 200-hour, 10,576-trajectory tactile dataset.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[CAP Fixes Humanoid Depth Sensor Failures Mid-Walk]]></title>
      <link>https://humanoidintel.ai/news/cap-continuously-adaptive-perception-blind-humanoid-locomotion</link>
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      <pubDate>Fri, 11 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[CAP paper proposes a single-stage denoising policy that handles corrupted depth on the Unitree G1 without switching sub-policies.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[FARM Reads Failure Signals from Frozen World Models]]></title>
      <link>https://humanoidintel.ai/news/farm-failure-monitoring-frozen-world-models-vla-jepa</link>
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      <pubDate>Fri, 11 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[FARM's 33,985-parameter readout hits 85.68 AUROC on failure detection using only frozen VLA-JEPA states.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[Wheeled Humanoid Motion Retargeting via 21-DOF Policy]]></title>
      <link>https://humanoidintel.ai/news/galaxea-r1-pro-wheeled-humanoid-motion-retargeting-pipeline</link>
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      <pubDate>Fri, 11 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[New pipeline converts SMPLX human motion into executable loco-manipulation for the Galaxea R1 Pro wheeled humanoid using a 21-dim policy.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[HuRo Dataset: 630K Episodes Lift VLA Task Completion to 80%]]></title>
      <link>https://humanoidintel.ai/news/huro-robotizing-human-videos-vla-pretraining</link>
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      <pubDate>Fri, 11 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[HuRo converts 630K human video episodes into robot training data, lifting VLA task completion from 51.5% to 80.3%.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[IMLE-VLA Hits 55 Hz with Single-Step Action Generation]]></title>
      <link>https://humanoidintel.ai/news/imle-vla-single-step-action-generation-55hz</link>
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      <pubDate>Fri, 11 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[IMLE-VLA replaces diffusion's iterative sampling with single-step cIMLE, hitting 55 Hz and 98.0% on LIBERO.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[Disentangling Habit From Physics in Robot World Models]]></title>
      <link>https://humanoidintel.ai/news/habit-physics-nuisance-robot-world-models-2026</link>
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      <pubDate>Thu, 10 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[New causal framework separates operator habit, physics, and observation noise in robot world models to improve low-shot transfer.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[HaWMPO Cuts VLA Hallucinations, Lifts G1 Success 12.5pts]]></title>
      <link>https://humanoidintel.ai/news/hawmpo-hallucination-aware-world-model-vla-policy-optimization</link>
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      <pubDate>Thu, 10 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[HaWMPO scores +15% on LIBERO and lifts Unitree G1 manipulation success from 67.5% to 80%.]]></description>
      <category>research</category>
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