Skip to content
#Data and simulation
Aug 12Wed
  1. OFweek Robotics61

    PaXini completes 1 billion yuan strategic round, total funding nears 4 billion yuan, relocates headquarters to Beijing

    PaXini disclosed the completion of a 1 billion yuan strategic funding round, bringing cumulative funding to nearly 4 billion yuan, while relocating its headquarters to Beijing and completing its conversion to a joint-stock company. The article analyzes its full-stack layout across tactile sensors, omni-modal data collection, dexterous hands, and robot bodies, stating that consumption of its self-developed tactile chips approached 1 million units in the past year, and that the PX-6AX GEN3 fingertip product supports up to 717 tactile signal outputs, a maximum frequency of 1000 Hz, IP68 protection, and a measurement lifespan exceeding 10 million cycles; the figures come from PaXini's laboratory.

  2. 拓斯达48

    Closing the full chain from scenarios to AI! Topstar's industrial data collection matrix achieves a major technical breakthrough

    After completing the deployment of virtual simulation data applications, Topstar has filled in its real-machine data collection capability and launched a real-machine multimodal data collection system. The system is centered on a self-developed high-precision multimodal data collection gripper, which can adapt to various robot models without joint mapping and supports six-degree-of-freedom high-precision pose tracking, with an average positioning error of ≤0.25% under normal operating conditions. It also simultaneously records multidimensional information such as visual images, motion trajectories, end-effector poses, and gripper actions, and is compatible with single-arm and dual-arm process teaching.

Aug 10Mon
Aug 3Mon
Jul 28Tue
  1. 北京智在无界科技有限公司64

    BeingBeyond releases Being-H0.8, the first implicit world action model to introduce touch in pretraining

    BeingBeyond has released Being-H0.8, which it calls the world's first implicit tactile world action model, unifying vision, touch, action, and future state changes into a single latent space, with pretraining on more than 500,000 hours of first-person human video.

    Why it matters: The model brings touch into large-scale pretraining along with a self-developed pseudo-labeling system, letting readers understand the path by which tactile data goes from a lab signal to a scalable pretraining resource.

Jul 27Mon
  1. 拓斯达38

    Topstar and Wuwen Zhike Build Industrial AI Capability Foundation, Completing a Key Piece of the Embodied Intelligence Data Loop

    Topstar and Wuwen Zhike have built a physical AI data loop platform for industrial handling scenarios, covering the full chain from virtual simulation, data annotation, and data organization to model training and real-machine evaluation. The platform uses Scan2Sim and Gen2Sim to generate training scenarios for multiple operating conditions and long-tail edge cases in batches, compressing the on-site commissioning cycle from "months" to "weeks"; real data uses automatic pre-annotation plus manual review, increasing annotation efficiency 10-fold. Topstar says it has connected the full process of data collection, simulation expansion, model training, and real-machine deployment, and that all its embodied intelligence robots can rely on the platform to complete standardized iteration.

Jul 24Fri
  1. 求之科技 · 微信公众号38

    Qiuzhi Technology's ROS Summer School "Embodied Intelligence VLA Bootcamp" concludes at Zhejiang Sci-Tech University

    The ROS Summer School "Embodied Intelligence VLA Bootcamp" organized by Qiuzhi Technology concluded at Zhejiang Sci-Tech University from July 20 to July 23, with more than 40 trainees from universities, research institutes, and enterprises taking part. The course used the AIRBOT Play six-axis robotic arm as its hands-on platform; participants completed motion planning with MoveIt2 and ran through the Real2Sim2Real pipeline using DISCOVERSE 3DGS rendering and MuJoCo simulation, then carried out data collection, model training, and deployment inference on the real robot, finishing with a group task challenge.

  3. 云启资本42

    Yunqi Quarterly Q2 | Midsummer, the future takes on more concrete forms

    Yunqi Capital released its Q2 quarterly report, disclosing progress by its portfolio companies in three areas: financing, products, and deployment: the post-investment valuations of X Square Robot and Zhineng Pingfang Technology both exceed 20 billion yuan, Stardust Intelligence completed a Series B round of over 1 billion yuan, and Nova Fusion has raised a cumulative 1.2 billion yuan.

Jul 22Wed
Jul 20Mon
  1. 石麻笔记 · 微信公众号74

    Interview with Dai Ruoli: ModalityNet compiles human data into learnable robot data

    Shima Notes conducted an in-person interview with Noitom founder Dai Ruoli, interpreting the ModalityNet dataset it has launched. The dataset contains three types of data that can be reused across embodiments: MOV large-space interaction data (about 8,000 hours, compared with about 70-plus hours for AMASS), OM dexterous manipulation data (sub-millimeter hand precision, including tactile and spatial audio), and ITW in-the-wild subjective vision data; the public portion is about 1/20 of the amount actually held.

Jul 15Wed
  1. 正行创新 Striding AI59

    Tsinghua and Striding AI propose self-supervised frame-level advantage modeling algorithm STEAM, achieving a 92.3% success rate on the towel-folding task

    Associate Professor Yu Chao's team at Tsinghua University, together with Striding AI, jointly proposed the self-supervised frame-level advantage modeling algorithm STEAM, which learns frame-level progress signals from the temporal order of expert demonstrations and scores expert data, robot rollouts, and human correction data frame by frame.

  2. LimX Dynamics61

    LimX Dynamics releases humanoid VLA model V³-0 alongside COSA 0.5

    LimX Dynamics released V³-0 alongside COSA 0.5, a humanoid VLA technology stack in its VLA-tools layer that supports mobile whole-body manipulation, running on the 43-DOF LimX humanoid robot Oli.

    Why it matters: The original text explains the architectural composition of V³-0 and its human-in-the-loop real-robot reinforcement learning loop, which lets readers understand where the mobile whole-body manipulation capability comes from.

Jul 14Tue
  1. RoboParty · 微信公众号75

    RoboParty Lab Established, Open-Sources Three Humanoid Robot Toolchains for Training, Control, and Data

    RoboParty announced the establishment of RoboParty Lab and open-sourced three humanoid robot toolchains: the supervised learning training framework MimicLite, the unsupervised reinforcement learning control framework UFO, and the motion retargeting tool hhtools.

    Why it matters: The three toolchains provide specific figures on training compute, time required, and the policies already integrated, which readers can use to assess their reuse value in their own R&D workflows.

  2. PsiBot/灵初智能81

    Lingchu Intelligence and PKU-Lingchu Joint Lab Release and Open-Source Dual Dexterous Hand General Manipulation Model and Full-Stack System EgoSteer

    Lingchu Intelligence and the PKU-Lingchu Joint Lab released and open-sourced the dual dexterous hand general manipulation model and full-stack system EgoSteer, comprising the data processing pipeline EgoSmith, the robotics technology stack Robot-Stack, and a world-model-enhanced VLA model.

    Why it matters: The original text presents a complete chain from human-hand data processing and real-robot correction to model architecture and experimental figures, allowing readers to assess its reproducibility value.

Jul 13Mon
Jul 11Sat
  1. Pieter Abbeel52

    ABC releases open robot data and training infrastructure; i2rt launches compatible ABC Box hardware kit

    ABC has released open data, training, and infrastructure for robots, along with its largest teleoperation dataset to date, and has systematically studied design decisions, pretraining, and post-training techniques. Pieter Abbeel shared and recommended i2rt's ABC Box robot kit, saying it is compatible with ABC's data and training infrastructure and easier to get started with; the link is https://i2rt.com/products/abc-box.

Jul 9Thu
  1. 蚂蚁灵波科技 · YouTube70

    Ant Lingbo Open-Sources Embodied Video Foundation Model LingBot-Video, Scoring 0.620 on RBench

    Ant Lingbo has open-sourced LingBot-Video, a MoE video foundation model for embodied intelligence. It uses a DiT plus sparse MoE architecture with 30B parameters and 3B activated at inference, and is claimed to be about 3 times more efficient than dense models.

    Why it matters: The material provides comparison scores on RBench and the scope of the open-source release, helping readers judge the starting point and usability of this embodied video model.

Jul 7Tue
  1. 智源研究院 · 微信公众号74

    BAAI releases multimodal representation world model Wujie·RoboBrain Orca

    BAAI has released the multimodal representation world model Wujie·RoboBrain Orca. Its core idea is to shift from predicting the next word, next frame, or next action to predicting the next world state: it first learns a unified latent world representation, then adapts to downstream tasks through three lightweight readout modules for text, images, and actions.

    Why it matters: The original text explains the training paradigm shift from predicting the next output to predicting the next state, as well as the approach of a frozen backbone plus lightweight readout modules, which is transferable to readers following the world model route.

Jul 1Wed
  1. 求之科技 · 微信公众号67

    GeoPredict makes VLA predict future trajectories and 3D geometry before generating actions

    The Chinese University of Hong Kong, Shenzhen and other institutions propose GeoPredict, which explicitly predicts end-effector and joint-level future trajectories before the VLA generates actions, and uses 3D Gaussian modeling for the geometry of the future workspace.

    Why it matters: GeoPredict incorporates future trajectory and 3D geometry prediction into VLA training, giving readers a spatial reasoning approach that does not increase inference overhead.

Jun 30Tue
Jun 28Sun
Jun 25Thu
Jun 24Wed
  2. Robot.com Holdings Inc.68

    Robot.com releases R-KNav 10,000-hour sidewalk navigation dataset and launches FoMo Challenge

    Robot.com has released the R-KNav dataset and launched the FoMo Challenge, inviting the community to train visual navigation models on real data from its R-kiwi sidewalk delivery robot fleet and to evaluate them in controlled tests on physical robots.

    Why it matters: The data comes from a long-running commercial delivery fleet rather than simulation, and the KPI criteria for physical-robot evaluation have been published, making it possible to assess the reusability of real-street navigation data.

Jun 20Sat
  1. Russ Tedrake59

    Russ Tedrake interprets the Ambient Diffusion Policy paper: the value of suboptimal data varies with noise level

    Adam's new paper proposes Ambient Diffusion Policy, which selectively learns robot policies from suboptimal data through a data-usage approach that depends on noise level. The authors note that when training denoising diffusion models, each data point is used multiple times at different noise levels, and a data point's value may differ by noise level. The method can extract value from a considerable portion of the OXE dataset that was previously discarded, and is complementary to pi0.7's approach of learning conditioned on data quality.

Jun 18Thu
Jun 16Tue
  1. Deep Robotics/云深处科技57

    Deep Robotics Lynx M20 Wheeled-Legged Robot Deployed for Inspection in Chengdu Underground Utility Tunnel

    Deep Robotics' wheeled-legged robot Lynx M20, equipped with a smart utility tunnel solution, has been deployed for inspection in nearly 26 kilometers of underground utility tunnels at Chengdu Future Science and Technology City. The robot combines wheeled and legged locomotion, can pass through passages as narrow as 50 centimeters, and supports autonomous charging and automatic return for 7×24-hour inspection. It integrates infrared temperature measurement, gas detection, high-definition cameras, acoustic collection, and other sensor modules, and works with Junyi Digital to carry a digital twin operations and maintenance system, enabling three-tier red, orange, and yellow alerts and a closed digital inspection loop.

Jun 15Mon
  1. 石麻笔记 · 微信公众号67

    In Conversation with Jianyuan Wang, First Author of VGGT: The Future of 3D Reconstruction Foundation Models and Robotic Spatial Perception

    This article is an interview with Dr. Jianyuan Wang, first author of VGGT, which won the CVPR 2025 Best Paper Award, and of VGGT-Ω, a CVPR 2026 Best Paper finalist. He is currently pursuing a PhD through a joint program between the Oxford Visual Geometry Group and Meta AI.

  2. New Scientist Robots56

    Reporter visits Physical Intelligence: progress and controversy on the general-purpose robotics path

    Physical Intelligence is developing a general-purpose control brain that can work across many kinds of robots, using a vision-language-action (VLA) model to teach robots tasks such as making coffee, folding clothes, and peeling vegetables, rather than focusing on a single machine as Tesla, Boston Dynamics, or Amazon do.

Jun 12Fri
  2. 石麻笔记 · 微信公众号62

    In conversation with Huang Wenlong: PointWorld and 3D world models

    Investor Shi Ma speaks with Stanford PhD student Huang Wenlong (advisor Li Feifei) about his PointWorld work and 3D world models. PointWorld uses 3D point flows to unify state and action representations, mapping different robots' joint actions into point cloud changes via URDF to address inconsistent actions across embodiments; training used the DROID and BEHAVIOR datasets, with annotations relying on FoundationStereo, VGGT, and CoTracker3.

Jun 9Tue
  1. Holiday Robotics60

    South Korea's Ministry of Science and ICT Launches Physical AI Leading Technology R&D Project, Investing 34 Billion Won Over Two Years to Advance World Model Localization

    South Korea's Ministry of Science and ICT held a launch briefing for the Physical AI Leading Technology R&D Project in Seoul on June 9, planning to invest 34 billion won over two years to jointly develop a Korean-style world model and domestic simulator with 10 industry-academia-research institutions including LG Electronics, aiming to raise robots' final action success rate by more than 20 percentage points compared with not using a world model, and planning to achieve an MVP within one year and eight months and conduct validation at manufacturing and logistics sites.

    Why it matters: The South Korean government has launched a project to localize core physical AI technologies; readers can learn about its investment scale, target metrics, and industry-academia-research division of labor.

Jun 6Sat
  1. 富唯智能31

    Fuwei Intelligence: AI large models plus digital twins empower industrial humanoid robot deployment

    The Fuwei Intelligence Fuzhi 1 and Fuzhi 2 are mass-produced industrial humanoid robots, each with a dual-arm rated payload of 8 kg. Fuzhi 1 is equipped with FW75 precision robotic arms and dual RGB-D depth cameras, with accuracy of ±0.02 mm, and focuses on fine assembly; Fuzhi 2 has FW65 heavy-duty robotic arms, three industrial cameras, and a 2.2-meter lifting column, and focuses on heavy-load transfer. Both robots share Fuwei's self-developed AI large model and digital twin simulation platform, and are suited to industrial scenarios including automotive, electronics, logistics, healthcare, new energy, and CNC machining.

Jun 5Fri
  1. PKU EPIC Lab61

    PKU EPIC Lab proposes LIMMT, a data-centric study for humanoid motion tracking, accepted to ICML 2026

    PKU EPIC Lab released LIMMT (Less Is More for Motion Tracking), which it describes as the first data-centric study for physics-based simulated humanoid motion tracking. The method defines motion data quality along three dimensions: physics feasibility, diversity, and complexity. Training on less than 3% of AMASS achieves better tracking performance than training on the full dataset, and the team also cleaned web-sourced mocap data. The paper has been accepted to ICML 2026; see arXiv:2606.06953.

    Why it matters: The paper presents a three-dimensional data quality framework and results from training on a small amount of data, offering a methodological reference for researchers working on humanoid motion tracking.

  2. Noble Machines · X16

    Noble Machines Moby simulation demo of navigation in construction scenes

    Noble Machines demonstrates its general-purpose robot Moby navigating a simulated construction environment and moving through obstacles. The simulation accelerates evaluation of real tasks and environments and screening of high-value use cases, helping customers identify target applications; Noble Machines and the customer then go through a discovery process and validate with Moby. The company invites customers interested in exploring deployment use cases to book a meeting at #Automate2026.

Jun 4Thu
Jun 3Wed