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Only First party#Robot models and learning
Jun 30Tue
  1. Figure AI63

    Figure 03 arrives at BMW Spartanburg plant for sequencing sorting tasks

    Figure AI announced that the Figure 03 humanoid robot has entered Hall 52 at BMW Group Plant Spartanburg, shifting from the sheet metal loading and unloading work previously done by Figure 02 to a sequencing sorting use case; Figure 02 took part in assembling 30,000 vehicles last year.

    Why it matters: The company has released details of Figure 03's deployment scenario at the BMW plant and of its Helix 02 drive, so readers can learn about progress in bringing humanoid robots from material handling to complex sorting.

Jun 25Thu
  1. HUMANOID63

    KinetIQ Ascend uses real-world reinforcement learning to boost humanoid robot manipulation throughput and success rate

    HUMANOID has launched KinetIQ Ascend, an end-to-end visual reinforcement learning method that operates under production deployment conditions, extending its KinetIQ framework to let robots improve manipulation skills through trial and error rather than relying solely on human demonstration; the company says this is the first such method publicly demonstrated on production-line humanoid robot manipulation.

    Why it matters: The original text provides specific throughput and success-rate figures for three industrial tasks and notes a pattern of predictable performance improvement with training duration, making it useful for assessing the practical value of real-world reinforcement learning on humanoid robots.

Jun 24Wed
  1. Stial/斯帝尔科技21

    STIAL Named to KPMG China Future Unicorn AI List's "Innovation Double 30 Enterprises"

    The KPMG China Future Unicorn AI List (Yangtze River Delta region) award ceremony was held in Shanghai on October 19. STIAL was selected as one of the "Innovation Double 30 Enterprises" for its AI embodied intelligent robot system for grinding scenarios. Its NextBrainAI Mogu Cloud system integrates a cognitive system with force, tactile, visual, and auditory perception, combines intelligent trajectory planning with intelligent process recipe generation, and achieves intelligent grinding based on deep learning and reinforcement learning.

  2. Harbin Institute of Technology Robotics62

    HIT's Zhu Yanhe Team Publishes Paper on Cooperative Reconfiguration for Self-Repair in Modular Robots

    Professor Zhu Yanhe's team at Harbin Institute of Technology (HIT) published a paper in the International Journal of Extreme Manufacturing (IJEM), proposing an autonomous fault-tolerant repair strategy for modular robots based on cooperative reconfiguration, which restores joint fault damage by changing morphology without backup module replacement. The method combines topological description and kinematic self-modeling, particle swarm optimization to search for target configurations, and an improved RRT cooperative reconfiguration algorithm. In experiments, the fault-tolerance upper limit was 7 times higher than that of fixed-configuration redundancy methods. HIT is the sole completing institution, and doctoral student Qi Jian is the first author.

    Why it matters: The paper presents a cooperative reconfiguration fault-tolerance strategy that requires no backup modules and data showing a 7-fold increase in the fault-tolerance upper limit, allowing readers to understand a concrete implementation path for self-repair in robot swarms under extreme environments.

Jun 23Tue
Jun 17Wed
  1. Sanctuary AI57

    Sanctuary AI extends Physical AI strategy to industrial robots, achieving 99.5%+ success rate on wire plugging task

    Sanctuary AI announced a task success rate of over 99.5% on a wire plugging production task at a global Tier 1 automotive supplier, with a cycle time of 2.54 seconds, validated against the customer's real-time production benchmarks. The company has shifted its strategy to deploying Physical AI on existing commercial robot hardware rather than waiting for humanoid hardware to reach mass production; the system handles flexible cables on a moving conveyor, with throughput matching the customer's production line level.

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 8Mon
  1. PKU EPIC Lab64

    KPGrasp: A Scalable Keypoint Flow Matching Method for Dexterous Grasp Generation

    PKU EPIC Lab proposes KPGrasp, a dexterous grasp generation method that combines an all-Euclidean 3D hand-keypoint parameterization with a Transformer flow-matching model to learn grasp priors from large-scale data, without contact losses or contact-based test-time optimization.

    Why it matters: The paper presents a new contact-loss-free grasp generation method and specific results on two benchmarks, letting readers compare it with existing methods and assess its approach.

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.

Jun 4Thu
  1. 1X Technologies61

    1X Establishes World Model Lab, Sam Sinha Appointed Head of World Models

    1X announced the formal establishment of the 1X World Model Lab, focused on large-scale pretraining of embodied world models, with the goal of accelerating the realization of fully autonomous humanoid robots. Sam Sinha, formerly a founding research scientist at Luma AI, has joined as Founding AI Researcher and Head of World Models.

    Why it matters: 1X officially outlined the World Model Lab's data approach and its full-stack in-house development stance, giving readers insight into its technical path toward autonomous humanoids.

Jun 1Mon
  1. Agile Robots/思灵机器人28

    Agile Robots gains early access to NVIDIA Cosmos 3 for physical AI simulation

    Agile Robots has obtained early access to NVIDIA Cosmos 3, with early simulation tests showing strong capabilities. The company will integrate Cosmos 3 for customers, offering new options for simulating, testing, training, and deploying physical AI, and is exploring the Cosmos-based NVIDIA Video Augmentation Skill for automated data curation, generation, and evaluation.

May 15Fri
  1. 富唯智能26

    2025 Guangzhou AI Innovation List | Fuwei Intelligence's GRID large model selected as an outstanding AI+Manufacturing case

    Fuwei Intelligence's embodied-intelligence industrial robot solution, built on its self-developed GRID large model, was selected for the 2025 Guangzhou Artificial Intelligence Innovation and Development List as an "Outstanding AI+Manufacturing Case" and was also named to the "Startup Potential List." The list is assessed under the leadership of the Guangzhou Municipal Science and Technology Bureau, with review covering five major dimensions including technological originality and implementation feasibility. The solution features multimodal perception, autonomous environment recognition, real-time intelligent decision-making, and adaptive motion control, and targets industrial scenarios such as intelligent sorting, flexible assembly, and material transport.

May 13Wed
  1. Noble Machines51

    Noble Machines Breaks Down Its Industrial Autonomous Learning Stack: Whole-Body Control, Task-Level Learning, and Runtime Error Correction

    Noble Machines published an article introducing its three-layer robot learning stack for industrial autonomy, along with on-site test results from GTC 2026: over four days, the same model simultaneously drove multiple Moby robots to complete two autonomous tasks at the NVIDIA booth and its own booth.

May 11Mon
  1. Lumos Robotics/鹿明机器人60

    Lumos Robotics completes several hundred million yuan A1 and A2 funding rounds, with Mitsubishi Electric leading both

    Lumos Robotics has completed several hundred million yuan in A1 and A2 funding. The A1 round was led by Mitsubishi Electric, with participation from Puhua Capital and Wuzhong Financial Holdings, among others. Mitsubishi Electric continued to lead the A2 round, with participation from Hundsun Electronics, Haigao Group, and Kunshi Investment, among others. The funding will be used for embodied large-model R&D and scenario expansion. After the funding, the company's cash reserves reached several hundred million yuan. Its flexible quality-inspection embodied intelligence solution, co-created with Mitsubishi Electric, has been put into trial use at Mitsubishi Electric's factory in China. Its self-developed Lumos Nexcore physical AI engine and bodyless data-collection system Lumos FastUMI Pro support industrial deployment and data feedback.

    Why it matters: The original text provides details on the funding structure and industrial partnerships, allowing readers to understand its industrial deployment path and data-collection technology layout.

May 8Fri
  1. Figure AI62

    Figure AI shows two Helix-02 humanoid robots collaborating to tidy a bedroom

    Figure AI demonstrated two humanoid robots equipped with Helix-02 collaborating to tidy a bedroom within two minutes, completing tasks such as opening a door, hanging clothes, putting away headphones, closing a book, taking out trash, pushing a chair under a desk, and making a bed together. The two robots run the same learned vision-language-action (VLA) policy, with no shared planner, message passing, or central coordinator; each infers the other's intent from its actions via its own cameras. The company says that to its knowledge this is the first demonstration of multi-humanoid collaborative mobile manipulation completed by a single learned neural network directly from pixels to actions.

    Why it matters: The official demonstration shows two humanoid robots driven by the same VLA system collaborating to tidy a bedroom, giving readers insight into an approach to multi-robot collaboration without a shared planner.

May 6Wed
  1. Genesis AI · YouTube32

    Genesis AI's GENE-26.5 Autonomously Performs Straw Flip at 1x Speed

    Genesis AI's robotic foundation model GENE-26.5 autonomously completed a continuous one-handed fine manipulation sequence: unwrapping a straw, flipping the straw with one hand, dropping it into a cup, and then handing the drink to a person. The entire sequence was executed autonomously and filmed at 1x speed, not teleoperated. The demo showcases fluid one-handed dexterous manipulation across multiple small, precise actions.

Apr 30Thu
  1. LimX Dynamics67

    LimX Dynamics Open-Sources FluxVLA Engine, a Standardized VLA Engineering Foundation

    LimX Dynamics has officially open-sourced FluxVLA Engine, a standardized VLA engineering foundation for embodied intelligence that covers the full pipeline from data and training to simulation evaluation and real-robot deployment.

    Why it matters: LimX Dynamics has officially open-sourced its VLA engineering foundation, which lets readers understand how unified configuration and real-robot deployment workflows lower the barrier to research and development.

Apr 29Wed
  1. Figure AI64

    Figure 03 production ramps up: BotQ capacity rises 24-fold in 120 days to 1 unit per hour

    Figure announced that its BotQ factory has delivered more than 350 third-generation humanoid robots, Figure 03, with takt time improving from 1 unit per day to 1 unit per hour, a 24-fold throughput increase in 120 days. The line is driven by self-developed manufacturing execution software and covers more than 150 networked workstations. First-pass yield for completed units exceeds 80%, the battery line's first-pass yield is 99.3%, more than 9,000 actuators have been produced, and each robot undergoes more than 80 functional verification tests before leaving the factory.

    Why it matters: The official figures give specific production and quality-control numbers and explain how fleet scale supports the deployment of perception-conditioned whole-body control.

Apr 22Wed
  1. PsiBot/灵初智能75

    Lingchu Intelligence releases Psi-R2 and Psi-W0, open-sources 1,000-hour full-modality human hand manipulation dataset

    On April 10, Lingchu Intelligence released Psi-R2, pretrained on human data, and the Action-Conditioned World Model Psi-W0, and open-sourced the first 1,000 hours of a full-modality human hand manipulation dataset, with total data reserves reaching 100,000 hours.

    Why it matters: The original text provides the division of labor between the two new models and the open-source data entry point, so readers can assess the feasibility of using human data for robot training.

Apr 20Mon
  1. PsiBot/灵初智能57

    Lingchu Intelligence Secures Investment from Guotou Xiandao and Jingxi Ruiling, Bolstering Embodied AI R&D and Commercialization

    Lingchu Intelligence announced the completion of a new funding round, with Guotou Xiandao and Jingxi Ruiling as investors; the funds will be used for core technology R&D and commercialization. On April 10, the company released its next-generation embodied AI models Psi-R2 and Psi-W0 and open-sourced a 1,000-hour full-modality human manipulation dataset, stating that Psi-R2 ranked No. 1 globally on the Molmospace benchmark; it will next advance the large-scale application of its dexterous manipulation solutions in logistics, industrial, and new retail scenarios.

  2. 普罗宇宙23

    Technology Empowers Intangible Cultural Heritage, Craftsmanship Passes Down Classics — ProUniverse Dabai Robot Appears at JD MALL

    The ProUniverse Dabai robot performed a dual-arm collaborative lacquer fan craft demonstration at the opening event of JD MALL (Wuhan Wangjiawan store), producing a customized lacquer fan within 1 minute. Its AI multimodal 3D vision and 2D industrial-grade positioning support sub-millimeter precision operation, and distributed learning enables rapid transfer of new scene skills. The event also introduced the "Craftsmanship Universe" plan, which, relying on the self-developed SDPAA parallelized data collection architecture and the InduThread-VLA large model, transforms traditional artisan skills into storable and replicable digital assets, with future expansion from crafts such as lacquer and sugar painting to precision assembly and high-end manufacturing fields.

Apr 16Thu
  1. Physical Intelligence77

    Physical Intelligence releases steerable general-purpose robot model π0.7, demonstrating compositional generalization

    Physical Intelligence has released the general-purpose robot model π0.7, which it says can perform a variety of dexterous manipulations with speed and robustness comparable to fine-tuned specialized models, and shows preliminary signs of compositional generalization on tasks not seen in its training data.

    Why it matters: The article uses two specific experiments, an air fryer and folding clothes with a UR5e, to show the actual performance of compositional generalization and cross-embodiment transfer, making it easier to judge the gap between general-purpose and specialized models.

Apr 15Wed
  1. Skild AI67

    Skild AI Acquires Zebra Technologies' Robotics Division to Advance Warehouse Deployments

    Skild AI announced the acquisition of Zebra Technologies' robotics division (formerly Fetch Robotics), and plans to deploy Skild Brain in warehouse settings to automate end-to-end fulfillment processes. Zebra's Symmetry Fulfillment scheduling platform has been validated in logistics environments, where it can coordinate tasks among robots and frontline workers; the company says the acquisition will accelerate its data flywheel and expand into more verticals and robot form factors.

    Why it matters: The acquirer itself explained the integration direction, so readers can judge how its platform and general-purpose models will be combined to enter warehouse settings.

Apr 13Mon
  1. 线性资本51

    UNICUS completes new round of several million USD led by Linear Capital

    Personalized manufacturing brand UNICUS (formerly Fangzai Photo Studio, Shenzhen Qianzhi Technology Co., Ltd.) announced the completion of a new round of financing of several million USD, led by Linear Capital, with JiuKun Venture Capital and Skyline Capital participating, along with personal participation from the founding team and founders of leading companies in the Maker sector; the funds will be used for building-block generation large model training, AI Agent development, and overseas market expansion.

Apr 11Sat
  1. 线性资本57

    Simple AI completes third funding round in six months, raising hundreds of millions of yuan, led by Linear Capital and Puhua Capital

    General-purpose embodied intelligent robotics company Simple AI announced the completion of its third funding round within six months, raising hundreds of millions of yuan, led by Linear Capital and Puhua Capital, with existing shareholders Junshan Capital, Shunwei Capital, and BV Baidu Ventures continuing to increase their investment; the funds will be focused on R&D of embodied robot brains and bodies.

Apr 10Fri
  1. PsiBot/灵初智能74

    Lingchu Intelligence Releases Psi-R2 and Psi-W0 Dual Models, Pretrained on 100,000 Hours of Human Data

    Lingchu Intelligence released two models, Psi-R2 and Psi-W0, which it calls the industry's first embodied intelligence models pretrained on human data at the 100,000-hour scale.

    Why it matters: The original article, written by the team itself, breaks down the dual-model architecture and data governance conclusions, offering a reusable path for human data utilization along with experimental evidence.

Apr 9Thu
  1. Zerith Robotics/零次方62

    Zero Power Robot completes over 100 million yuan funding round led by Runze Group

    Zero Power Robot announced the completion of a new funding round of over 100 million yuan, led by Runze Group, with Ningbo Dongli, Jieli Angel, and Pinghu Zexin participating. The company said its order count has exceeded 100 million yuan and revenue is in the tens of millions, with stable monthly mass production of 100 units, and validation completed in more than 20 landmark scenarios nationwide; the article also introduced its technological progress including the 4D augmented model ZERITH-SDA and the brain-inspired dual-stream asynchronous execution architecture ZERITH-V2.

    Why it matters: The company self-reports its funding details and order scale, and explains its scenario deployment path and data augmentation method, offering insight into its commercial and technological layout.

Apr 2Thu
  1. Tokyo Robotics · YouTube28

    Torobo humanoid's human-like walking and whole-body control

    Tokyo Robotics demonstrated human-like walking, whole-body teleoperation, and motion tracking on its custom-built Torobo humanoid. The control policies are trained through large-scale parallel reinforcement learning, and policies learned in physics simulation, once deployed to the real hardware, achieved dynamically stable whole-body motion. The company says it will continue improving motion stability in both software and hardware, and plans to introduce AI for autonomous task execution.

  2. Sanctuary AI55

    Sanctuary AI demonstrates zero-shot in-hand manipulation with hydraulic dexterous hand

    Sanctuary AI demonstrated zero-shot in-hand manipulation in the real world with its proprietary hydraulic hand: a policy trained entirely in simulation continuously reoriented a lettered cube to a target pose ten times in a row without dropping it. The operation relied solely on the fingertips with no palm support, requiring simultaneous stable grasping and approach to the pose target. The original text states that the hand has a relatively high number of active degrees of freedom enabling finger abduction, and that hydraulic actuation and compact hydraulic valves offer a path toward industrial-grade humanoid dexterous manipulation.

Mar 24Tue
  1. Agile Robots/思灵机器人66

    Agile Robots and Google DeepMind announce strategic partnership to integrate Gemini Robotics models into industrial robots

    Agile Robots SE and Google DeepMind announced a strategic research partnership to combine the Gemini Robotics foundation models with Agile Robots' industrial robot platform and develop adaptable, reasoning-capable robots. The partnership initially focuses on industrial manufacturing scenarios where reliability and scale are critical, forming a data flywheel through deployment, data collection, model training, and iteration; Agile Robots says it has installed more than 20,000 robot solutions worldwide.

    Why it matters: The partnership focuses on industrial deployment and data feedback for training, giving readers insight into the path to real-world adoption when foundation models are connected with robot manufacturers.

  2. Berkeley AUTOLAB68

    CaP-X: Benchmarking and Improvement Framework for Robot Manipulation Coding Agents Released

    Teams including Berkeley AUTOLAB propose CaP-X, an open framework for systematically studying Code-as-Policy agents in robot manipulation, centered on the interactive environment CaP-Gym and CaP-Bench, which evaluates 12 frontier models.

    Why it matters: The original text presents a systematic evaluation framework for Code-as-Policy agents and the finding that test-time scaling can mitigate abstraction dependence, offering reference value for research on coding-agent manipulation control.

  3. Dobot/越疆机器人64

    Dobot begins mass production delivery of third batch of full-size industrial humanoid robot ATOM

    Dobot Robotics has officially begun mass production delivery of the third batch of its full-size industrial humanoid robot ATOM, deploying it to frontline industrial applications worldwide. ATOM runs on the self-developed DOBOT-VLA model, which combines vision, language, and action for autonomous decision-making; its joint modules have undergone nearly 10,000 cycle tests, and it supports coordinated scheduling with wheeled and multi-legged robots on a unified platform.

    Why it matters: The source, provided by the party involved, describes progress on the third batch's mass production delivery and its deployment in real scenarios, giving readers a sense of the pace of its industrialization.

Mar 20Fri
Mar 19Thu
  1. Physical Intelligence60

    Physical Intelligence proposes RLT: efficient online reinforcement learning for fine manipulation

    Physical Intelligence proposes a new method called RL tokens (RLT), in which a vision-language-action model (VLA) outputs a special token to interface with a lightweight online reinforcement learning policy, improving the speed and success rate of fine manipulation phases with only a small amount of real data.

    Why it matters: The original clearly explains the interface design between the VLA and lightweight online reinforcement learning and provides speedup data on four tasks, so readers can assess whether this type of method applies to their own fine manipulation tasks.

  2. Skild AI75

    Skild AI partners with ABB Robotics, Universal Robots, and NVIDIA to deploy Skild Brain

    Skild AI announced partnerships with ABB Robotics and Teradyne-owned Universal Robots and MiR to integrate its general-purpose model Skild Brain into industrial robots, eliminating task-by-task programming and using post-training fine-tuning with a small amount of task data.

    Why it matters: Skild AI describes its own partnership deployment approach with ABB, UR, and NVIDIA and assembly task details, letting readers understand how its general-purpose model enters production lines.