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#Data and simulation
Oct 19Mon
  1. HuggingFace Daily Papers70

    Ropedia W0: Scaling loco-manipulation world foundation models across embodiments

    The paper proposes Ropedia W0, an egocentric loco-manipulation world foundation model spanning humans and robots with diverse embodiments. The research builds the Xp-Data dataset, containing 10,000 hours of egocentric human data and 3,000 hours of robot data, with unified multimodal annotations and quality control; camera poses encode locomotion and projected skeletons encode manipulation, with robot skeletons combining each embodiment's forward kinematics and manual keypoint annotations.

  2. HuggingFace Daily Papers59

    PVBench: Quantifying the Physical Plausibility of Video Generation with Object-Level Physical Measurements

    Researchers propose PVBench, a physical video benchmark that quantitatively measures the physical plausibility of generated videos across 46 dimensions in seven domains, covering instruction and semantic fidelity, behavioral and causal consistency, perceptual and temporal quality, geometric and spatial consistency, material properties and field states, kinematic and spatiotemporal persistence, and mechanics and conservation laws.

  3. 36Kr Embodied Intelligence44

    Embodied AI Data Industry Booms, Data Assets See Value Revaluation

    The embodied AI data industry is booming due to robot training demand. Real-machine data, bodyless collection data, and simulation data have become the three major categories of training data, corresponding respectively to production methods such as robot operations in training grounds, human collection in motion-capture cages, and virtual simulation generation. As the industry rapidly expands data scale, practitioners believe data quality and data evaluation standards are crucial.

Oct 18Sun
  1. 量子位74

    VAST open-sources real-time world model EdenLive, over 24 FPS at 720P on a single RTX 5090

    VAST has released and open-sourced its real-time world model EdenLive, opening up the model weights, inference code, technical report, and an end-to-end demo. According to VAST, on a single consumer-grade Nvidia RTX 5090 GPU at 720P, the 5B model generates at over 24 FPS, can generate continuously for minutes at a time, and has end-to-end latency in the hundreds of milliseconds.

  2. 深蓝AI · 微信公众号73

    HKUST-GZ UniWAM: Fusing VLA and WAM into a Single Transformer, Dual SOTA in Simulation and on Real Robots

    A team at HKUST-GZ proposes UniWAM, which uses a Mixture-of-Transformers (MoT) architecture to integrate physical reasoning, future visual generation, and action prediction into one model. Built on three expert modules—Qwen3-VL-2B-Instruct, the Wan2.2-TI2V-5B backbone, and an action predictor—and paired with the EgoANT pipeline for automatic annotation of egocentric human video, it is jointly pretrained on human data, robot demonstrations, and VQA data.

  3. Guyuehome56

    RoboTTT uses fast weights and context scaling to help robots remember operations from five minutes earlier

    RoboTTT targets a structural flaw in robot foundation models: mainstream policies such as VLA struggle to remember things that happened earlier. It proposes using fast weights and context scaling to improve long-horizon memory. The original text is an excerpt from an introduction and does not provide full experimental details.

  4. Guyuehome42

    In-Depth Analysis of Simulation Data Collection Technology: A Bridge from the Real World to Robot Intelligence

    Niantic Spatial and Flexion have jointly launched a simulation data collection solution based on 3D Gaussian Splatting, aimed at alleviating the contradiction in humanoid robot training: millions of interactions are needed, yet the physical world does not allow repeated trial and error. The solution reconstructs real scenes via 3D Gaussian Splatting, providing a simulation data source that allows repeated trial and error for robot learning.

  5. Guyuehome58

    EgoWAM Switches the Supervision Channel for Dual-Arm Manipulation from Actions to World State

    EgoWAM examines a concrete deployment conflict in dual-arm robotic manipulation: first-person human data collected by Project Aria glasses is cheap and abundant, but retargeting human hand trajectories into robot actions for behavior cloning (BC) is difficult, so this work switches the supervision channel from actions to world state.

  6. 钛媒体74

    Local Governments Become Major Robot Customers: The Funding Loop and Data Price Collapse Behind the Boom of 70 Training Grounds

    The article examines how local governments have become the largest buyers of robots: by the end of June 2026, more than 70 embodied intelligence training grounds had been built nationwide, with 46 under construction or planned, covering 18 provincial-level administrative regions; from 2024 to June 2026, localities issued more than 40 related policies in total.

  8. HuggingFace Daily Papers58

    BiDex-100: A dual-arm dexterous manipulation benchmark covering 100+ simulation tasks

    The paper proposes BiDex-100, a simulation benchmark for dual-arm dexterous manipulation comprising 106 tasks organized along five capability axes: generalization, instruction following, limited demonstrations, long horizon, and memory. Each task is paired with an out-of-domain variant featuring controlled visual and spatial changes to assess robustness.

  10. Guyuehome60

    Reproduction and Evaluation of ACT on the MuJoCo Dual-Arm Block Handover Task

    A complete reproduction of the Action Chunking Transformer (ACT), implemented with LeRobot, on the MuJoCo dual-arm block handover task, covering the CVAE and action-chunking derivations, frame-by-frame comparison against the dataset to validate the inference pipeline, and a 20-episode deterministic closed-loop evaluation with a comparison of execution modes.

  11. Guyuehome48

    AirCombat: Tactical Decision-Making and Swarm Engagement Simulation for Multi-UAV Air Combat

    AirCombat uses rule-based agents to simulate UAV air combat swarm engagements ranging from 1v1 to 10v10, covering close-range dogfights and ten-versus-ten scenarios. The system breaks air combat decision-making into 48 discrete actions and introduces an abstract weapon engagement model and a formation target assignment mechanism to explain the sources of tactical decision-making complexity in multi-aircraft confrontations.

  12. 3D视觉工坊 · 微信公众号12

    "3D Vision from Beginner to Mastery" Knowledge Planet: Nearly 20 video courses covering industrial 3D vision/SLAM/3DGS/embodied intelligence

    The "3D Vision from Beginner to Mastery" Knowledge Planet has been running for nearly 9 years and now has more than 6,400 3D vision practitioners. It includes nearly 20 core video course tracks, covering industrial 3D vision, SLAM, 3DGS, autonomous driving, drones, embodied intelligence, and other directions.

Oct 17Sat
  1. 机器之心 · 微信公众号70

    HKU's EgoWild2Dex trains dual-arm robot on 538.9 hours of "extremely dirty" human data, with under 1 hour of real-robot data

    The University of Hong Kong's MMLab team proposes EgoWild2Dex, which directly trains a dual-arm dexterous robot on 538.9 hours of unscripted human first-person manipulation data, using under 1 hour of real-robot data per downstream task; across three long-horizon tasks—unpacking a parcel, fixing ornaments with a hot glue gun, and making a cold drink—the average success rate is 96.7%.

  2. 36Kr Embodied Intelligence61

    Hesai launches 3D world data engine Kosmo, including spatial camera Kosmo One and cloud platform Kosmo World

    Hesai Technology has launched Kosmo, a 3D world data engine consisting of Kosmo One, the world's first 8K ultra-HD AI spatial camera, and Kosmo World, an AI-driven cloud platform. The former captures spatial geometry, color, texture, and pose information of real environments; scanning an ordinary indoor scene of 100 square meters takes about 15 minutes.

  4. GitHub Robotics Topic57

    Breaking Bellman 1.1 released, all 17 robot levels now open

    Breaking Bellman 1.1 is released, with all 17 levels open and a robot appearing in every world, including playing slot machines in a casino, learning cliff walking by jumping down into a canyon, balancing a broom on its head (CartPole), choosing doors in the fog, finding a charger on the goal grid, and swinging a pendulum; the arm levels add a scene with a workbench and a coffee cup to avoid, while the robot dog fetches a ball in a park.

  5. 机器之心 · 微信公众号64

    Hesai launches Kosmo 3D world data engine, spatial camera scans 100 square meters in about 15 minutes

    On October 14, Hesai launched the Kosmo 3D world data engine, comprising the Kosmo One spatial camera and the Kosmo World cloud platform. Kosmo One integrates lidar, an imaging system, and a high-precision IMU into a single device. Under ordinary indoor conditions, it can complete a scan of 100 square meters in about 15 minutes, and its custom lidar can render tennis racket string holes spaced about 5 millimeters apart.

  6. 新智元 · 微信公众号71

    Scale AI and Elorian Release HSS Benchmark to Test Visual Intuition: Humans 93.1%, Strongest Model GPT-6-astra Only 53.6%

    Scale AI, in partnership with Elorian, released a new benchmark called Humanity's Sixth Sense (HSS) to test intuitive visual reasoning in multimodal models: 20 human participants scored 93.1%, while top-ranked GPT-6-astra reached only 53.6% even at maximum reasoning effort, and the median across 25 models was 30.9%.

  7. Reddit r/robotics38

    2-hour reinforcement learning simulation of a quadruped robot dog in MuJoCo

    In a training platform built on a self-made MuJoCo physics simulator, the developer trained a quadruped robot dog simulation using reinforcement learning with motion imitation (style reference motions). Trained for only 2 hours on a MacBook Air CPU (no GPU), it learned a keyframe trot gait and balance. Joints are limited by a realistic hobby servo model in torque, speed curve, backlash, and latency, making the gait smoother than pure reinforcement learning. The simulation supports WASD-driven multidirectional control.

  8. 机器人全球资讯 · 微信公众号42

    Xinjiang's first embodied intelligent robot production line to be completed in April next year

    Xinjiang Dadao Industrial Investment Co., Ltd. has begun construction of an embodied intelligence live training center and application validation base, becoming the first enterprise in Xinjiang to integrate embodied intelligent robot R&D and testing. Its production and assembly line is expected to be completed in April next year, at which point it will be able to customize to customer scenario requirements and deliver embodied intelligent products in multiple varieties, small batches, and multiple batches.

  9. 机器人全球资讯 · 微信公众号53

    Embodied AI Robot Training Ground at Nanjing Air-Ground Digital Intelligence Block Set to Open Soon

    The embodied AI robot training ground in the Air-Ground Digital Intelligence Block of Nanjing Jiangning Development Zone is in the final stages of construction and will be put into use soon. Multiple quadruped and wheel-legged robots are undergoing pre-launch testing. The training ground covers about 5,000 square meters and features standardized multi-terrain, combined real-scene, and interactive open areas, replicating real environments such as factories, urban operations and maintenance, and emergency operations. It is jointly built by Nanjing Communications Group and Nanjing Shengxun Information Technology Co., Ltd.

Oct 16Fri
  1. GitHub Embodied AI Topic65

    PhySim Gate v0.1.0 released: a regression gate tool for simulation results such as robotics

    PhySim Gate v0.1.0 is the first release of a simulator-agnostic regression gate tool for robotics, embodied AI, autonomous driving, and drone simulation results. Given a baseline run, a candidate run, and gate.yaml, it judges metric by metric whether the candidate has degraded and explains why, outputs JSON, JUnit XML, and a standalone HTML report, and returns CI-usable exit codes (0 pass, 1 regression, 2 input error, 3 inconclusive or invalid, 4 internal error).

  6. 机器之心 · 微信公众号69

    From Hardware and Data to Models: How Sharpa Systematically Advances Dexterous Manipulation

    In a conversation with Synced, Sharpa's academic lead Zhang Kaifeng outlined three main threads for advancing dexterous manipulation: human-centered data collection, high-frequency tactile low-level control that decouples motion from interaction, and tactile-anchored cross-embodiment representation learning.

  7. AI前线 · 微信公众号78

    Google releases Gemini 4 Argon physical reasoning model, connecting the full robotics R&D chain

    Google has released Gemini 4 (Argon), positioned as a general physical reasoning model focused on interaction with the physical world, covering the full robotics lifecycle from control execution and simulation reconstruction to data annotation and self-improvement. On the ERQA embodied reasoning benchmark, Argon scored 87%, surpassing Claude Opus 5.5 (82.3%) and GPT-6 Astra (81%); in the AA-Omniscience test, its hallucination rate was 15%, lower than the 51% and 59% of the latter two.

    Why it matters: The article breaks down the model's specific uses and measured figures across the robotics R&D chain in four layers: control, simulation, data quality inspection, and self-improvement.

  9. Robotics & Automation News64

    Skild AI trains S1 model to play soccer via over 140 years of simulated self-play, then transfers it to humanoid robots

    Skild AI demonstrated a self-play training method in which its S1 robot foundation model learned through more than 140 years of simulated soccer matches in Nvidia Isaac Sim, without relying on human demonstrations. In simulation, the policy successively learned to recover from falls, dribble past opponents, shield the ball, and tackle, and was then transferred to physical humanoid robots for soccer-kicking demonstrations. The company says the method has been extended to everyday robotic tasks, and early experiments with four-agent passing plays have been conducted.