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2026.10.17 · Sat

#具身智能

#具身智能

First-party

Direct announcements from model vendors, companies and research institutions on their official sites, blogs and accounts.

10/14Wed
  1. Google DeepMind82

    Google DeepMind Introduces Gemini 4 Argon for Robotics

    Google DeepMind introduces Gemini 4 Argon, a general-purpose physical reasoning model for robot control, simulation reconstruction, physical understanding, and self-improvement. Google DeepMind reports an 87% ERQA score using pure reasoning and a simulation-generated training example that raises real-world robot success from 56% to 75% while reducing completion time from 35s to 24s. Argon is available today to Google AI Ultra subscribers through Google AI Studio and Google Antigravity, and through the paid Gemini API tier using gemini-4-argon in the Interactions API.

    Why it matters: The simulation-to-hardware example provides a concrete basis for assessing how generated training episodes can improve robot task success and completion speed within a reported setup.

9/24Thu
  1. Microsoft Research62

    Microsoft Research: offloading physical-AI inference from robots can improve task performance and battery life

    Microsoft Research systematically measured mobile-robot manipulation workloads and found that moving physical-AI inference from an onboard GPU to an edge or cloud GPU can improve task performance and extend battery life.

    Why it matters: Microsoft Research measured robot inference workloads and reports performance and battery-life data for offloading inference from onboard hardware to edge or cloud GPUs.

9/22Tue
  1. NVIDIA Blog62

    NVIDIA releases Isaac ROS 5.0 to advance agentic, open-source robotics development

    At ROSCon, NVIDIA released Isaac ROS 5.0 with new agent workflows and platform support to help developers build, customize, and deploy robotics applications faster.

    Why it matters: The source lists Isaac ROS 5.0's agent skills and platform support, helping readers assess how much of the robotics development workflow can be automated.

7/30Thu
  1. Google DeepMind71

    Google DeepMind releases Gemini Robotics ER 2 embodied-reasoning model

    Google DeepMind has released Gemini Robotics ER 2, positioned as the robot's high-level brain: it converses with people, understands the physical world, and plans multi-step tasks before handing execution to a lower-level VLA model. It can also call tools such as Google Search natively.

    Why it matters: The official release gives concrete figures for ER 2's progress classification and temporal localization, along with access details, helping readers assess its limits on long tasks.

7/28Tue
  1. Google DeepMind80

    Google DeepMind releases Gemini Robotics 2 for full-body robot intelligence

    Google DeepMind has released Gemini Robotics 2 with three models: Gemini Robotics 2, a vision-language-action model for translating visual and language input into motion; Gemini Robotics ER 2 for embodied reasoning; and Gemini Robotics On-Device 2, which runs locally on devices.

    Why it matters: The article explains the three models' roles and access points, helping readers assess pathways to full-body robot control and multi-robot collaboration.

7/21Tue
  1. Hugging Face Blog62

    Hugging Face releases Grabette, an open system for recording robot manipulation data

    Hugging Face has released Grabette, a low-cost, open-source handheld gripper system for recording robot-manipulation demonstrations without a robot or teleoperation rig. It has a wide-angle fisheye camera and an RGB-D camera for policy-view recording and 6-DoF trajectory tracking, respectively. The hardware bill of materials is about €490; the companion robot-side gripper, Gripette, costs about €120.

    Why it matters: The source describes the full open pipeline from handheld-gripper recording to LeRobot datasets, helping readers assess how the barrier to collecting manipulation data is changing.

7/8Wed
  1. Mistral AI71

    Mistral AI releases Robostral Navigate embodied-navigation model

    Mistral AI has released Robostral Navigate, its first embodied-navigation model. The 8B model uses a single standard RGB camera, with no LiDAR or depth sensor, and achieves a 76.6% success rate on R2R-CE validation unseen—9.7 percentage points above the best single-camera approach and 4.5 points above the best systems using depth or multiple cameras.

    Why it matters: The source reports navigation success using a monocular RGB camera and describes the training approach, giving a view of how sensor requirements for embodied navigation are changing.

7/7Tue
  1. Hugging Face Blog74

    LeRobot v0.6.0 released: imagine, evaluate, improve

    Hugging Face has released LeRobot v0.6.0, adding world-model policies (VLA-JEPA, FastWAM, LingBot-VA), a new set of VLA models (GR00T N1.7, MolmoAct2, EO-1, EVO1, Multitask DiT), and a unified reward-model API (Robometer, TOPReward) to the robotics-learning loop.

    Why it matters: The release brings world-model policies, a reward-model API, and six simulation benchmarks into one CLI, giving readers a view of how production-ready the robotics-learning loop is becoming.

4/13Mon
  1. Google DeepMind71

    Google DeepMind releases Gemini Robotics-ER 1.6

    Google DeepMind has released Gemini Robotics-ER 1.6, a major upgrade to its reasoning-first robotics model. It improves spatial reasoning and multi-view understanding and adds the ability to read complex instruments such as pressure gauges and level meters.

    Why it matters: The source details changes in spatial reasoning, multi-view understanding, and instrument reading, along with access information, giving a view of progress in high-level robot reasoning.

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