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#Data and simulation
Oct 30Fri
  1. 机器之心 · 微信公众号76

    PokeBot releases embodied API RoboAPI, world-action model Poke-Aurora debuts

    PokeBot released its first model product, RoboAPI, in the early hours of October 30. It is a publicly accessible, out-of-the-box embodied API: after developers connect and adapt a robotic arm, they need neither to collect data nor train models, and can issue commands with a single prompt to execute tasks the model was not specifically trained on.

    Why it matters: Readers can learn how a publicly accessible embodied API hands zero-shot generalization capability over to external developers for testing, as well as its success-rate data from its own evaluation.

  2. 机器之心 · 微信公众号75

    Shanghai Jiao Tong University and others propose VaM: using value prediction for task-progress memory, achieving over 95% success rate in 4-hour continuous carton assembly

    Shanghai Jiao Tong University, Shanghai Innovation Institute, and others propose Value as Memory (VaM), which feeds the recent prediction sequence of a value model into the action policy as task-progress memory, combined with an offline-to-online real-robot reinforcement learning pipeline. In a carton assembly task, VaM ran autonomously and continuously for 4 hours with a task success rate above 95%. Ablations show that compared with a version without the value cache, the final task success rate improved by 29.4%; the online RL approach improved average success rate by 32.8% across three tasks and reduced the real-world time cost per gradient step by 57.8% on average.

  3. 机器人产业应用 · 微信公众号58

    Boyin Hechuang officially opens Suzhou headquarters and joins Bosch supplier system

    On October 29, Boyin Hechuang, jointly incubated by Boyuan Capital and Galaxy General, officially opened its 10,000-square-meter Suzhou headquarters, covering the full chain from R&D, simulation testing, scenario validation, and small-batch trial production to customer delivery, and has entered the Bosch supplier system. The company says its BW10 series, equipped with the VLA model, achieves efficiency of about 800–1,000 items per hour in logistics sorting, and that BW10-Lite has been deployed in the in-plant logistics scenario at United Automotive Electronic Systems' Shanghai plant. Under its plan, the company aims to gradually raise annual production capacity to 4,000 units by 2027, and its German subsidiary is in the preparatory stage.

  4. CVer · 微信公众号71

    Fudan and NTU propose SimpleVLN: native multimodal large model sets new SOTA in vision-language navigation

    A team from Fudan University and Nanyang Technological University, among others, proposed SimpleVLN, which performs vision-language navigation without changing the core structure of a multimodal large model or adding dedicated navigation modules, relying only on observation filtering, action-chunk decision-making, and three-stage training with SFT, DAgger, and reinforcement learning.

  5. 新智元 · 微信公众号74

    Daxiao Robotics and NTU S-Lab Release Interactive World Model Mundo

    Daxiao Robotics, in collaboration with Nanyang Technological University's S-Lab, has released Mundo, an interactive world model built for specific environments that integrates 3D scene reconstruction, physics simulation, and video generation. The system uses scene code to record object weight, center of mass, and friction coefficients, computes motion and collisions with a 960Hz MuJoCo physics engine, and then renders visuals combined with on-site photos; inputting 1 to 12 phone photos is enough to reconstruct a 3D space that supports pushing, pulling, and collisions.

  6. 爱范儿40

    Tencent launches smart cockpit TAI agent and AI organizational efficiency solution for the automotive industry

    At the smart mobility session of its Global Digital Ecosystem Summit in Shenzhen, Tencent released an upgraded TAI agent solution consisting of the TAI cockpit assistant, mobility service agent, content and entertainment agent, and cross-device continuity service. It integrates Yuanbao full-duplex end-to-end voice, Yuanbao Search, and the Hunyuan large model, and uses Tencent Maps, the WeChat Mini Program ecosystem, and WeChat Pay to complete task execution and transaction loops.

  7. Xbotics具身智能实验室 · 微信公众号88

    Infinigence AI, Tsinghua and AgiBot propose collective experience learning (CEL) paradigm, validated on 96 robots

    Infinigence AI, together with Tsinghua University and AgiBot, proposed the collective experience learning (CEL) paradigm and completed prototype validation on 96 robots. In a phone packaging task, a policy trained with CEL completed 120 tests on two robots of the same model that did not participate in training, with success rate rising from 79.2% to 98.3%; when the number of robots participating in learning increased from 16 to 96, the test success rate rose from 86.7% to 98.3%.

    Why it matters: Readers can learn about a training paradigm that lets robots share successes and failures and reduces reliance on human demonstration, as well as its validation results on 96 real robots.

  8. 帕西尼 · 微信公众号56

    CAS Institute of Automation proposes tactile-enhanced grasp-and-insertion framework, achieving 67% success rate at 0.05 mm clearance

    The team led by Cheng Long at the Institute of Automation, Chinese Academy of Sciences, proposed a tactile-enhanced full-pipeline learning framework for grasping and insertion, achieving a 67% success rate at 0.05 mm clearance and a 60% reduction in peak contact force; the paper was accepted to IROS 2026. The research uses the PaXini PX6AX GEN3 multi-dimensional tactile sensor as its core sensing hardware, integrated into a seven-axis robotic arm, covering five geometric shapes and three clearance levels of 1, 0.25, and 0.05 mm. Under the same conditions, the tactile-free IL+RL approach achieved a 52% success rate, while the pure imitation learning approach achieved 0.

  9. 36Kr Embodied Intelligence71

    Critical Point releases OmniGlove Pro data-collection glove and begins mass-production delivery

    At the dexterous manipulation sub-forum of AgiBot Innovation Day, Critical Point released the OmniGlove Pro data-collection glove and began mass-production delivery. It focuses on "real-robot-ready" data that aligns human hands with real robots using high-precision EMF positioning and full-hand tactile collection.

  10. 古月居 · 微信公众号58

    Open X-Embodiment and RT-X: A Practical Guide to Cross-Embodiment Transfer for Large-Model Robot Policies

    This article provides a systematic walkthrough of cross-embodiment transfer practice with Open X-Embodiment and RT-X, covering RLDS data-format unification, the RT-X model architecture, pretraining, fine-tuning, and deployment on new robots. It presents RLDS conversion scripts, a PyTorch implementation of an RT-1-based model, and training techniques such as temperature sampling and embodiment-weighted loss, and it documents six categories of pitfalls, including slow data loading, poor cross-embodiment performance, and action-space mismatch, along with corresponding solutions.

  11. 机器人daily · 微信公众号62

    CAS Institute of Automation and Paxini collaborative study: tactile-enhanced reinforcement learning achieves sub-millimeter precision assembly

    A team led by Cheng Long at the Institute of Automation, Chinese Academy of Sciences, published research at IROS 2026 using tactile-enhanced reinforcement learning to improve the success rate and stability of sub-millimeter precision insertion. The approach first uses Diffusion Policy imitation learning to reach the hole opening, then SAC reinforcement learning to complete the insertion, and handles real-world tactile noise through tactile baseline compensation and balanced sampling grouped by torque.

  12. 36Kr Embodied Intelligence82

    AgiBot, Tsinghua, and Infinigence AI Release CEL Collective Experience Learning Paradigm, Achieving Autonomous Cluster Evolution with 96 Real Robots

    On October 30, AgiBot, together with Tsinghua University and Infinigence AI, released the collective experience learning paradigm CEL, which draws on the real operational trajectories of robot peers as its source of experience, accompanied by the FERT failure-guided experience retrieval fine-tuning algorithm and the FATS fault-tolerant asynchronous training system. Across five real-world tasks—flower arranging, clothes folding, phone charging, stool assembly, and phone packaging—CEL-trained policies all exceeded the average level of 6 human teleoperators, leading by up to 16.7 percentage points. In the phone packaging task, the number of robots participating in training expanded from 16 to 96, and the success rate rose from 86.7% to 98.3%.

    Why it matters: Readers can learn about a collective learning paradigm that draws on the real trajectories of peers as its source of experience, as well as the success-rate changes in cluster training with 96 real robots.

  13. 3D视觉工坊 · 微信公众号88

    Infinigence AI, Tsinghua and AgiBot propose Collective Experience Learning (CEL), validated on 96 robots with 98.3% success rate

    Infinigence AI, together with Tsinghua University and AgiBot, proposed the Collective Experience Learning (CEL) paradigm and completed prototype validation on 96 robots. In a phone packaging task, policies trained with CEL completed 120 tests on two robots of the same model that did not participate in training, with the success rate rising from 79.2% to 98.3%; when the number of robots participating in learning increased from 16 to 96, the test success rate rose from 86.7% to 98.3%.

    Why it matters: Fault-tolerant asynchronous training across a 96-robot real-machine cluster and failure-guided experience retrieval provide a reproducible system and scale-benefit data for Collective Experience Learning.

  14. 3D视觉工坊 · 微信公众号55

    HandBot-S2 multi-sensor fusion 3D scanner launched, with optional 3DGS SDK and in-house calibration source code

    HandBot-S2 is a 3D spatial scanner with open hardware and data. It integrates 3D LiDAR, front, left, and right trinocular cameras, an IMU, and RTK, achieves millisecond-level synchronization through hardware triggering, and provides calibrated intrinsic and extrinsic parameters.

  15. 雷科技84

    AgiBot and Tsinghua Release CEL Collective Experience Learning Paradigm, Achieving Autonomous Swarm Evolution with 96 Real Robots

    AgiBot, together with Tsinghua University and Infinigence AI, released the collective experience learning paradigm CEL, which lets robots use the success and failure trajectories of their peers as learning material, with humans only responsible for judging outcomes. Across five real-world tasks—flower arranging, clothes folding, phone charging, stool assembly, and phone packaging—policies trained with CEL all exceeded the average level of 6 human teleoperators, leading by up to 16.7 percentage points; in the phone packaging task, the number of robots participating in training expanded from 16 to 96, and the success rate rose from 86.7% to 98.3%.

    Why it matters: AgiBot and Tsinghua released the CEL collective experience learning paradigm, validating with 96 real robots that increasing the number of robots can directly improve task success rates.

  16. HuggingFace Daily Papers72

    OpenFlyV2 releases onboard vision-language-action model for aerial perception and navigation

    OpenFlyV2 is a unified onboard vision-language-action architecture that uses a shared vision-language representation to support semantic understanding, language-grounded perception, spatial reasoning, and continuous flight control within a single model. The model generates action chunks of 12 waypoints each entirely onboard at 10 Hz on an NVIDIA Jetson Orin NX, and transfers zero-shot from simulation to a real quadrotor, achieving a 48% navigation success rate in four real environments without using real aerial training data.

  17. OFweek Robotics58

    Will data collection become a "sacrifice" of embodied intelligence?

    The article notes that in less than two years, 106 humanoid robot data collection centers have been built nationwide in China. Some robot companies inflate reported revenue through a "sell equipment—buy back data" arrangement, and Mech-Mind founder Shao Tianlan has publicly mentioned such irregularities. Data prices have fallen from over 200 yuan per hour last year to over 100 yuan this year, and collection methods are shifting from real-robot teleoperation to bodyless collection, reducing the need for data collection centers to purchase robots. The article also cites Forbes' questioning of Figure AI's valuation bubble and a speculation that industry consolidation is expected to become concentrated between the second half of 2026 and 2027.

  18. Leiphone Robotics78

    Columbia's Yunzhu Li team presents FlexiTac open-source tactile sensor progress at IROS 2026

    At IROS 2026, Columbia University's Yunzhu Li team presented progress on FlexiTac, an open-source flexible piezoresistive tactile sensor platform, a year and a half after its open-source release. The sensor can be assembled in 3 minutes, bent and cut, and wrapped around gloves, fingertips, or robot skin. The team has integrated it into LeRobot and modified the UMI handheld device to add tactile recording, enabling synchronized visual-tactile data collection and policy pretraining. ADI is advancing a commercial version with tactile resolution five times that of a human finger, manufactured at scale using semiconductor fabrication processes.

    Why it matters: From sensor design and simulation calibration to UMI data collection, it presents a complete technical path toward scaling tactile perception.

  19. Reddit r/humanoidrobotics18

    Can virtual worlds let AI learn to help robots before entering the real world? A discussion on Google Genie 4 and robot training

    A discussion proposes that robots could first practice obstacle avoidance and grasping different objects in virtual environments before working in real warehouses, using Google Genie 4's interactive world model as a potential research tool. Genie 4 is not a robot control system, and whether interactive world models can play a greater role in robot training remains to be explored.

  20. Leiphone Robotics62

    Xingyuan Intelligence Releases Cross-Embodiment Data Engine Chorus, Turning Human Manipulation Videos into Robot Training Data

    Xingyuan Intelligence has released Chorus, a cross-embodiment data engine for robot pretraining that can convert human manipulation data collected by devices such as smart glasses, chest-mounted cameras, wrist cameras, and UMI into training data adapted to different robot embodiments.

  21. Leiphone Robotics55

    IROS 2026 observations: How many hurdles must dexterous hands clear to move from demo to productivity?

    Leiphone observed on site at IROS 2026 that dexterous-hand demonstrations have shifted from simple grasping to complex contact, long-horizon tasks, and deformable-object manipulation. Yang Sicheng, founder of Yuansheng Intelligence, proposed that deployment must clear three thresholds: balanced system capability, long-term stable operation, and acquisition of high-quality manipulation data.

  22. 量子位72

    Tsinghua University, Infinigence AI, and AgiBot propose collective experience learning CEL, validated on a 96-robot cluster

    Tsinghua University, Infinigence AI, and AgiBot jointly proposed the collective experience learning (CEL) paradigm, which lets robots share the successful experience of their peers rather than relying only on human demonstrations, and validated it on a cluster of 96 real robots. Two robots that did not participate in training were tested 600 times in total across five tasks—flower arranging, clothes folding, phone charging, stool assembly, and phone packaging—with 15 failures, for an overall success rate of 97.5%, all exceeding the average level of 6 human operators; the success rate on the phone packaging task rose from 79.2% to 98.3%.

  23. 智东西69

    Critical Point's dexterous hand completes 72-step industrial POC, 8.5 minutes per operation approaches human level

    At the Dexterous Manipulation sub-forum of AgiBot Innovation Day, Critical Point connected live to the Wolong Hill factory to present industrial POC results for a robotic arm plus dexterous hand. The system continuously completed a 72-step process including loading and unloading, barcode scanning, grasping a screw gun, tightening and removing screws, and pressing buttons. Phase-one task success rate reached 98%, with 8.5 minutes per operation, close to the roughly 8 minutes for a human, and it can run continuously for 8 to 12 hours.

  24. 钛媒体58

    Hesai launches Kosmo One spatial camera and Kosmo World cloud platform

    Hesai Technology launched Kosmo One, a handheld 3D spatial data capture device integrating lidar, an 8K imaging system, and a high-precision IMU, on October 14, alongside the Kosmo 3D world data engine and the Kosmo World cloud platform. Kosmo World reconstructs raw data into three spatially aligned formats: 3DGS, Mesh, and Depth. A typical indoor scene of about 100 square meters can be scanned in roughly 15 minutes. Hesai said it aims to move from hardware revenue toward data and model services, building a spatial model digital asset platform that customers can pay to use.

  25. 36Kr Embodied Intelligence60

    Qiyuan Robotics launches PrimeSim world model and tops WorldSimProbe LIBERO leaderboard

    Qiyuan Robotics has launched PrimeSim, a world-model simulator for robot training, and topped the WorldSimProbe LIBERO leaderboard. PrimeSim builds an interactive, trial-and-error, continuously learning virtual world for robots, used for policy validation and reinforcement learning. In tests, reinforcement learning with it raised policy success rate from 61.7% to 73.2%.

  26. OFweek Robotics65

    Maxinsights (Haiyu Shuwei) completes $30 million seed round, betting on real-world robot training data collection

    Silicon Valley-based Chinese physical AI company Maxinsights (Chinese entity Haiyu Shuwei) announced the completion of a $30 million seed round led by Peak XV, with participation from Tola Capital, South Park Commons, Ince Capital, and Alumni Ventures. All funds will go toward real-world robot training data collection.

  27. OFweek Robotics82

    X-Era AI Tuoyuan Zhihui releases open-source 4D world action model E0.5, with out-of-distribution real-robot success rate surpassing π0.5

    X-Era AI Tuoyuan Zhihui released the open-source native 4D world action model E0.5, which uses a 3D foundation model as its backbone and integrates future 3D geometry prediction directly into action learning. On the AgileX Piper dual-arm robot and the Zerith H1 humanoid robot, after pretraining on about 160,000 robot trajectories, E0.5 achieved overall average success rates of 85.0% and 88.3%, respectively, improving on π0.5 by 13.3 and 26.7 percentage points; its out-of-distribution average success rates were 73.3% and 76.7%.

    Why it matters: The original text provides a comparison of E0.5 and π0.5 success rates on out-of-distribution real-robot tasks, which readers can use to judge the effect of 3D geometry supervision on manipulation generalization.

  28. HuggingFace Daily Papers75

    TinyAstral: Transferring a self-evolving harness to small generalist manipulation agents

    TinyAstral proposes a two-stage method: first, freeze an open-weight teacher model and use recursive self-improvement (RSI) to have frontier LLM agents read the teacher's trajectories and propose harness modifications, with each modification accepted only if it passes a paired statistical test; then freeze the final harness and distill a small student model.

  29. OFweek Robotics71

    Sharpa unveils D01 humanoid robot, W02 dexterous hand, and AE01 data glove at IROS 2026

    At IROS 2026, Sharpa released three fully self-developed new products: the D01 humanoid robot with full-body electronic skin, the W02 dexterous hand with full-palm tactile sensing and 21 active degrees of freedom, and the AE01 exoskeleton data glove, which captures hand movements with 22 encoders and returns tactile feedback.

  30. 机器科学55

    RoboScience's Shao Lin Presents Cross-Embodiment Dexterous Manipulation Path from D(R,O) Grasp to FingerEye at Unitree Ecosystem Conference

    Shao Lin, founder of RoboScience, spoke at the 2026 World Physical AI Conference and Unitree Partner Ecosystem Conference, presenting a cross-embodiment dexterous manipulation technology path from the ICRA 2025 Best Paper D(R,O) Grasp to the T(R,O) Grasp series and then to the FingerEye visuotactile framework.

  31. Reddit r/robotics62

    PhAIL launches robot policy competition: top 10 after two simulation rankings advance to real Franka finals

    The PhAIL team and Nebius have launched a robot policy competition. Participants package their policies as Docker submissions, which are first scored in two simulations: MolmoSpaces and RoboLab starting November 16. In December, the top 10 will run the same image on a real Franka. The tasks resemble the DROID benchmark but use a different dataset.

  32. Reddit r/robotics78

    PrismaX shares π0.5 policy transfer across YAM devices: fine-tuning ablations, latency bug, and 16GB VRAM deployment

    The PrismaX team shared its practice of transferring a π0.5 policy trained on one YAM device to another YAM device, covering three parts: fine-tuning ablations, latency troubleshooting, and VRAM compression. On fine-tuning, training only the action expert yielded a 51% grasp rate and a 12% drop rate; full fine-tuning gave 89% and 53%; r=128 LoRA gave 84% and 59% while using 32GB. Strong lighting roughly halved the performance of the checkpoint trained only on the action expert.

    Why it matters: The original post provides details on fine-tuning ablations, latency troubleshooting, and VRAM compression for π0.5 policy cross-device transfer, which can be reused on existing equipment in small labs.

  33. CMU Robotics Institute62

    CMU proposes Wiggle and Go: estimating physical properties of ropes by wiggling to plan manipulation

    A team at CMU's Robotics Institute has proposed the Wiggle and Go system, in which a robot first briefly wiggles a rope or cable while an overhead camera records how the waves propagate; a computer vision algorithm then tracks the motion and estimates the object's physical properties, which are used to plan subsequent actions without repeated trial and error. The model is trained entirely in simulation, and properties are then estimated from the motion of real ropes being wiggled to improve prediction accuracy on real hardware. The research has been accepted to the 2026 Conference on Robot Learning (CoRL) and will be presented next month in Austin; it is partly funded by the U.S. National Science Foundation.

    Why it matters: The method estimates a rope's physical properties from a single wiggle and then plans actions accordingly, offering a transferable approach to deformable object manipulation.

Oct 29Thu
  1. 差评X.PIN · 微信公众号58

    Google DeepMind releases world model Genie 4, supporting real-time audio-video generation and scene modification

    Google DeepMind has released Genie 4, a new-generation world model that extends single-session world coherence from 1 minute in the previous generation, Genie 3, to 2 minutes, and becomes Google's first real-time world model with native support for synchronized audio-video generation.

  2. 机器人前瞻 · 微信公众号58

    WeRide subsidiary JingShuo Technology completes 70 million yuan pre-A funding round to build out world models

    WeRide disclosed that its subsidiary JingShuo Technology has completed a 70 million yuan pre-A funding round, with participation from Jiayu Capital, HKSTP (Hong Kong Science and Technology Parks), Sirius Capital and others; the investors together hold approximately 3.38%. JingShuo Technology has self-developed the integrated data-model platform WorldEngine, the world model GENESIS-Robotics and the data asset engine SkillForge, and has accumulated 500,000 hours of high-precision data, 50 million structured task segments and 200+ scenario skill packages.

  3. 机器人前瞻 · 微信公众号62

    Juqiao Industries completes hundred-million-yuan Series A funding, led by Ant Group, for fabric electronic skin

    Shandong-based flexible fabric tactile sensing company Juqiao Industries announced the completion of a hundred-million-yuan Series A funding round, led by Ant Group, with Lingyi Venture Capital, Weihai Gangrong, and Qingdao Hexin participating. The funds will be used for large-scale mass production and delivery of fabric electronic skin and for R&D in tactile and multimodal sensing technologies.

  4. 机器人前瞻 · 微信公众号58

    Tsing Standard releases automotive-grade first-person data collection solution Tsing-Ego PRO

    Tsing Standard released the automotive-grade first-person data collection solution Tsing-Ego PRO during SAECCE 2026. It uses 8-camera vision capture across the head and both wrists, supports 1080P global exposure and hardware synchronization, and achieves end-to-end synchronization accuracy of ≤1ms.

  5. 未来机器人网 · 微信公众号78

    Zhiyuan's Peng Zhihui: First-Half Revenue Near 2 Billion Yuan, 9,700 Humanoid Robots Shipped for Over 43% Global Share

    Peng Zhihui, co-founder, president, and CTO of Zhiyuan Robotics, disclosed at the 2026 Zhiyuan Innovation Day that in the first half of 2026 Zhiyuan shipped 9,700 humanoid robots, accounting for more than 43% of the global humanoid robot market, with revenue for the period approaching 2 billion yuan; as of September, cumulative output of general-purpose embodied robots surpassed 20,000 units.

    Why it matters: Zhiyuan disclosed first-half shipments of 9,700 units and revenue near 2 billion yuan, and introduced a new metric measuring commercialization by effective intelligent work hours, offering a way to track the pace at which humanoid robots move from demonstrations to delivery.

  7. 36氪 · 微信公众号36

    AI companies snap up "sky-high" data: Google in talks to buy Spirit Airlines internal records for tens of millions of dollars, $5,000 per math benchmark question

    Google offered $10 million to buy the internal records of bankrupt airline Spirit Airlines, including about 100 million emails and 500 million Microsoft Teams messages, to improve AI models. AI data company micro1 announced it will spend $1 billion over the next 12 months to buy or license operational data from enterprises and build reinforcement learning environments. Mathematicians are paid about $5,000 per question to supply AI with high-difficulty benchmark questions, and about 91% of Mercor's $614 million in first-half revenue came from foundation model companies.