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#Robot models and learning
Oct 29Thu
  1. HuggingFace Daily Papers55

    QUAN: Quaternion Approximate Networks Improve Image Classification and Oriented Object Detection

    The paper proposes Quaternion Approximate Networks (QUAN), which approximate quaternion convolution through Hamilton product decomposition using real-valued operations, paired with custom CUDA kernels to achieve rotation-equivariant image classification and object detection. The authors also propose Independent Quaternion Batch Normalization (IQBN) to stabilize training and extend quaternion operations to spatial attention mechanisms.

  2. The Humanoid Hub27

    Tesla Cancels Thanksgiving Investor Tour; Optimus Data Collection and 'Academy' Plan Draw Attention

    Tesla did not invite major investors to tour the Fremont factory this Thanksgiving as it has in past years, a move interpreted as extending the confidentiality period for the Optimus facility. Sources cited by Scobleizer say human data collection is 'massive in scale,' covering both home and factory scenarios; data collection operator positions appeared at Tesla about three years ago, requiring workers to wear 30-pound equipment.

  3. Reddit r/robotics65

    RynnUnify: 16B unified embodied model combines physical understanding with long-horizon visual planning

    The authors propose RynnUnify, a 16B unified embodied model that combines embodied understanding with long-horizon visual planning through video-language interleaved reasoning. The model covers spatial reasoning, physical prediction, and grounding capabilities, linking physical world understanding with visual anticipation across subtasks. The post also provides links to the code and paper.

Oct 28Wed
  2. APPSO · 微信公众号71

    Google DeepMind releases world model Genie 4, extending single simulation to 120 seconds

    Google DeepMind has released Genie 4, a new-generation world model that extends single interactive simulation duration from about one minute to two minutes and supports native audio generation for the first time. Genie 4 introduces Gemini to plan actions while it generates the environment in real time; in a demo, Gemini 4 Argon breaks a task into consecutive steps, and Genie 4 simulates the Apptronik Apollo humanoid robot playing checkers.

  4. 机器人全球资讯 · 微信公众号70

    AgiBot releases embodied Agent framework Genie Master; Genie G2 works and evolves in a convenience store

    AgiBot has released its embodied Agent framework Genie Master. Equipped with this framework, Genie G2 has taken a job in a real convenience store, where it does not rely on manual demonstrations or debugging; it autonomously identifies the causes of failures, adjusts its strategies, and accumulates experience, continuously improving on tasks such as packaged hot-food preparation, picking, and restocking, achieving self-evolution without a human in the loop.

  5. 机器人前瞻 · 微信公众号58

    Stardust OS Robotics Hackathon concludes: 16 of 17 teams' apps ran on real robots

    The Stardust OS Robotics Hackathon finals concluded in Shenzhen, with 16 of 17 teams' apps moving from simulation to real-robot testing, a real-robot rate of 94%. The competition centered on generating apps from a single sentence; across three stops it drew 47 teams, with entries covering tasks such as follow-cam photography, elderly care, and remote avatars. Stardust Intelligence uses AOS to connect external tools such as GPT-6 and Claude along with its in-house Lumo model, and to dispatch the capabilities of its cable-driven robot body downward.

  6. The Robot Report78

    WorldOracle releases action-conditioned world model benchmark; seven models show deviations between predictions and real execution

    Princeton University, UT Austin, the University of Toronto, NVIDIA, and AgiBot jointly launched WorldOracle, an action-conditioned world model benchmark that uses the same initial frame and action sequence to compare model predictions with real execution.

    Why it matters: The benchmark compares world model predictions frame by frame against real execution of the same actions and releases failure samples, making it easier to identify sources of model deviation over long sequences.

  7. 甲子光年 · 微信公众号45

    2026 Jiangsu AI+Science and Engineering Hackathon concludes: Agnes Harness supports 20 teams' AI4S prototypes

    The finals of the 2026 Jiangsu Province AI+Science and Engineering Innovation Practice Hackathon (University Group) have concluded. 536 teams registered and 20 advanced to the finals, with all projects built on Agnes Harness, the open-source agent development and execution infrastructure from Agnes.

  8. AI前线 · 微信公众号78

    Google DeepMind Releases World Model Genie 4, Supporting 24 FPS Real-Time Interaction and Native Audio

    Google DeepMind launched its next-generation world model Genie 4 on October 27 local time, calling it its most realistic and interactive world model to date, with a single generated interactive experience lasting up to 2 minutes, compared with 1 minute for the previous generation, Genie 3.

    Why it matters: Google is connecting language models' planning capabilities to real-time world generation, which lets readers understand a new approach to synthetic training grounds for embodied intelligence.

  9. 36氪 · 微信公众号84

    Google DeepMind releases world model Genie 4, supporting real-time interaction and native audio

    Google DeepMind released its next-generation general world model Genie 4 on the evening of the 28th. It can generate and modify interactive scenes in real time based on prompts, sustaining a single coherent world for about 2 minutes at roughly 24 frames per second.

    Why it matters: Genie 4 combines real-time world simulation, native audio, and multi-step reasoning, which lets readers judge that robot training environments are shifting from manual modeling to generative simulation.

  10. 36氪 · 微信公众号11

    AGIBOT GO-3 Nano Preview Tops RoboDojo Benchmark Leaderboard

    AGIBOT's GO-3 Nano Preview has topped the latest RoboDojo embodied intelligence benchmark leaderboard with an average score of 61.90 and an average success rate of 56.42%, surpassing GPT-6 Astra. The model ranked first in all three sub-dimensions: fine manipulation (78.65), long-horizon execution (68.21), and open-ended semantic understanding (61.71).

  11. 硅星人Pro · 微信公众号78

    Google DeepMind releases world model Genie 4, integrated with Gemini for real-time generation and task reasoning

    Google DeepMind has released Genie 4, a new-generation world model that supports real-time generation of explorable virtual worlds and simultaneously generates physics effects, character movements, and native audio. Genie 4 is integrated with Gemini 3.8 Flash as a real-time guiding Agent, responsible for understanding goals, observing the environment, and planning next steps; in the demo, it simulated robotic arm operation in a virtual laboratory.

    Why it matters: Google released the Genie 4 world model, demonstrating its collaboration with Gemini to plan and simulate robot task execution in virtual environments, offering a look at a new way world models can be used for robot training.

  12. 机器之心 · 微信公众号58

    Chaoyan Intelligence releases 35B model Apex-35B-V1.0, leading Recursive Flint on 18 of 21 benchmarks

    Chaoyan Intelligence, founded by Chen Yongchao, an assistant professor at Tsinghua University's School of Artificial Intelligence, has released its first 35B model, Apex-35B-V1.0. It was trained and post-trained on Qwen3.6-35B-A3B, balancing general capabilities such as coding and agents with AI research, computational science, and robot simulation tasks.

  13. 机器之心 · 微信公众号73

    Google DeepMind releases world model Genie 4, supporting real-time control and native audio

    Google DeepMind has released Genie 4, its fourth-generation world model, which can generate dynamic environments in real time; users can control characters or the camera with the keyboard and use natural language to change the weather and add objects and characters. Genie 4 is Google's first world model to natively generate real-time audio, and it also improves physics simulation such as aerodynamics and collisions as well as the naturalness of character movements.

  14. 雷科技56

    Google releases Genie 4 world model: supports real-time interaction, can generate robot training scenarios

    Google has released a research preview of its world model Genie 4, which natively supports multimodality, can change the environment and introduce new objects and characters through instructions during generation, and lets existing characters react. The model is integrated with Gemini, with Gemini Omni anchoring the simulated visual behavior logic to the real world. It is currently open only to invited testers and will later open first to Ultra subscribers.

  15. 新智元 · 微信公众号80

    Google releases world model Genie 4, with three Gemini models jointly driving robot actions

    Google DeepMind has released Genie 4, a new-generation general-purpose world model that natively generates sound and improvised dialogue for the first time, sustaining a single coherent world for about 2 minutes at roughly 24 frames per second of real-machine footage. The model uses a hybrid world-model architecture: Gemini 3.8 Flash handles real-time control, while Gemini 4 Argon breaks tasks into 22-step action instructions, driving an Apollo robot to play checkers and, in simulation, controlling a UR5 robotic arm to perform pipetting operations.

    Why it matters: Google has released the Genie 4 world model, with three Gemini models jointly driving robot action decomposition; readers can learn how world models are used for robot training.

  16. CVer · 微信公众号78

    Google releases world model Genie 4, supporting real-time generation and collaborative reasoning with Gemini

    Google DeepMind has released Genie 4, a new-generation world model that supports real-time generation of explorable virtual worlds, simulates physics and character movements, and natively generates ambient sound effects and dialogue. Genie 4 connects to Gemini 3.8 Flash as a real-time guidance agent, with Gemini planning tasks, observing feedback, and adjusting strategies. In the demo, it simulated robotic arm experimental operations and the Apptronik humanoid robot Apollo playing checkers in the generated environment.

    Why it matters: Google released the Genie 4 world model, demonstrating its ability to collaborate with Gemini to plan and simulate robots executing tasks in virtual environments.

  18. 人形大讲堂 · 微信公众号62

    Three cross-embodiment papers examined: body, motion, and environment data still need manual translation

    The article examines three cross-embodiment research papers published between October 24 and 26, arguing that cross-embodiment is more like translation than a spontaneous model capability. MimicAll uses a structured body-condition table covering 16 series and 4,096 body variants.

  19. Guyuehome58

    Jumper: Dynamic Jumping Control for a Crab Robot Based on Reference Motion and Residual Reinforcement Learning

    Jumper uses a reference-guided residual reinforcement learning method to control dynamic jumping in a crab robot. The reference motion records only the nominal trajectory, and the policy learns only the corrections to the reference commands. In this method, the takeoff impulse determines the launch velocity, the ballistic trajectory determines the airborne phase, and the official policy is used to complete jumping and boundary tests.

  22. 中国机器人网 · 微信公众号60

    Toyota advances humanoid robot strategy, plans to deploy 400,000 robots

    Toyota is advancing its humanoid robot strategy, planning to deploy 400,000 robots, backed by $6.4 billion in annual investment for factory automation. Walden Robotics, spun off from Toyota's AI robotics business, has completed a $300 million funding round at a post-money valuation of $1.1 billion, and its general-purpose robots are already deployed at Toyota's North American factories. A foundation model developed by Toyota Research Institute can convert high-level instructions into real-time physical actions and motor control; it has been used in Boston Dynamics' Atlas, and Eley, Toyota's self-developed 50-kilogram-class humanoid robot, will also run on this model.

  23. OFweek Robotics72

    XPeng's robotics business completes over $900 million first funding round at $6.3 billion post-money valuation

    XPeng Group's robotics business has completed a first funding round of over $900 million at a post-money valuation of $6.3 billion, led by IDG Capital with participation from Gaorong Ventures, and with Tencent and Alibaba joining as strategic investors. The funds will be used for software and hardware R&D, training and iteration of physical AI models, data collection, construction of mass-production facilities, and global commercialization. The IRON humanoid robot has 76 degrees of freedom across its body and 21 degrees of freedom per hand, carries 3 Turing AI chips, and has 2250 TOPS of on-device compute; mass production is planned for the end of 2026, with external deliveries to begin in 2027.

  25. 量子位65

    Physical Intelligence in talks for at least $1 billion in new funding at a valuation of up to $20 billion

    US robotics AI company Physical Intelligence is in talks for a new funding round of at least $1 billion, with a post-money valuation expected at about $20 billion, a sharp rise from its $5.6 billion valuation last November. The company has no commercial revenue to date and has not mass-produced its own robots; its core focus is general-purpose robot foundation models that adapt to third-party hardware. It has iterated from π0 to π0.7 and this month launched a beta API for its robot foundation model, offering model fine-tuning and inference services.

  26. 量子位55

    Wika releases high-quality dataset for embodied intelligence-enabled construction machinery

    Wika Mobile Control released the "High-Quality Dataset for Embodied Intelligence-Enabled Construction Machinery" at the 10th Xuzhou Artificial Intelligence Conference 2026, and it is now available on data repositories including Hugging Face. The first phase of the dataset has 36 million frames, covers 12 typical operation scenarios, and synchronizes five dimensions of data—vision, LiDAR, pose, force feedback, and joystick input—using a unified timestamp. Wika says real-machine data collection for excavators costs about 5,000 yuan per hour, and training a usable model roughly requires data on the order of 100,000 hours.

  27. 极客公园63

    From Stanford Research to Red Sea Corals: How LingBot Models Are Entering the Foundation of Global Embodied AI

    Geek Park reviewed how the LingBot model series from Ant Group's embodied AI unit Robbyant has been adopted in academia, open-source communities, and industrial toolchains. Stanford's OpenWAM uses the LingBot-VA architecture as a reference implementation, and a KAIST team used LingBot-VLA as a teacher model to raise its student model's single-step inference success rate from 35.3% to 51.2%.

  28. HuggingFace Daily Papers78

    RynnWorld-Latent: A Cross-Embodiment World Model Conditioned on Universal Latent Actions

    The research team proposes RynnWorld-Latent, a cross-embodiment video world model that uses the 3D-grounded latent actions of RynnLAM as a shared conditioning interface, enabling joint pretraining on human interaction videos, robot demonstrations, and simulation data.

    Why it matters: This work proposes using universal latent actions as a shared cross-embodiment conditioning interface, allowing human videos, robot demonstrations, and simulation data to jointly pretrain a world model.

  29. 智东西62

    iFlytek Releases SparkAudio 1.0 Speech Foundation Model

    During its 2026 Global 1024 Developer Festival, iFlytek released SparkAudio 1.0, a speech foundation model trained entirely on domestic compute. It supports text and speech dual-modal input with text output, and can perform speech transcription, multilingual translation, multi-dialect recognition, environmental sound recognition, speaker separation, sentiment analysis, and complex audio question answering.

  30. HuggingFace Daily Papers66

    PDRVLA: A Vision-Language-Action Model with Physical Dynamics Representations

    PDRVLA introduces a lightweight Physical Dynamics Module that extracts physical tokens from vision-language features to condition action generation, without requiring online future-video generation. The module learns by directly predicting future RGB, depth, and optical-flow features, with auxiliary supervision from a frozen pretrained video world model. Training uses only public data, expanded through human-to-robot synthesis, subtask annotation, and embodied chain-of-thought (ECoT) annotation.

  31. Yaskawa70

    Yaskawa Electric and GAZOO Racing to Bring AI Autonomous Welding Robot Technology to GR KART Manufacturing Site

    Yaskawa Electric and Toyota GAZOO Racing have jointly developed AI-driven autonomous robot production technology, with deployment beginning in September 2026 at the Gamagori GR KART workshop. The technology builds on the SFA method (Sequence Freezing Arc Welding) jointly developed by the two parties in 2024, and uses MOTOMAN NEXT robots equipped with GPUs and AI to autonomously recognize the state of pipe frames, complete welding, confirm and correct quality, and analyze appearance images, welding sounds, and various data in an integrated manner.

    Why it matters: Yaskawa and GAZOO Racing are extending their SFA welding experience into an AI autonomous welding line, and it has already gone into actual production at the GR KART workshop, offering a view of how welding automation moves from validation to the mass-production floor.

  32. 芯东西73

    Google releases world model Genie 4, capable of simulating aerodynamics and collisions with native audio generation

    Google released its next-generation world model Genie 4 on October 28, capable of simulating physical processes such as aerodynamics and collisions, and natively generating music, ambient sound, and interactive dialogue. The model combines capabilities from the Gemini series, with Gemini 3.8 Flash breaking down multi-step tasks in a loop, and Google also demonstrated it combined with Gemini Robotics to simulate an Apptronik Apollo humanoid robot playing checkers.

  33. arXiv cs.RO62

    SCRIM: Quantifying State Criticality in Imitation Learning

    The authors propose SCRIM, a state criticality measure that uses an adversarial perturbation policy and a value critic to estimate the worst-case degradation in downstream value caused by small perturbations to expert actions, scoring each demonstration state. These scores can be used to reweight behavior-cloning losses or to select compact, high-value subsets of demonstrations, reducing training data while maintaining performance. The method is evaluated on a variety of simulated and real robot manipulation tasks, and the paper was accepted to CoRL 2026.

  34. arXiv cs.RO62

    Goal2Pixel: A Vision-Language Navigation Method That Grounds Goals to Pixels

    Goal2Pixel proposes a pure pixel paradigm that reformulates vision-and-language navigation in continuous environments (VLN-CE) as navigable pixel grounding: the model predicts navigable pixels on the image plane, which are then back-projected into 3D waypoints for forward movement, while turning and stopping are encoded by auxiliary left, right, and bottom regions.

  35. arXiv cs.RO62

    AWARE: Action-Entropy-Weighted and Attention-Guided Retrieval of Observation Evidence for Vision-Language-Action Models

    The authors propose AWARE, a training-free, plug-and-play module for Vision-Language-Action (VLA) models that tracks layer-wise uncertainty via element-wise action entropy and retrieves observation evidence into the feed-forward networks' key-value memory through associative memory lookup.