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#Data and simulation
Oct 28Wed
  1. arXiv cs.RO71

    OpenJaws: An open-source hardware UMI framework for generalist manipulation, using stereo localization to improve demonstration accuracy

    OpenJaws is a fully open-source sensorized UMI hardware and software framework that pairs a modular 3D-printed gripper with a low-cost stereo camera to recover metric camera trajectories, improving action-label localization accuracy in handheld demonstrations. The authors also propose UMI-Loc-Bench-v1, a benchmark for quantifying the real-world localization accuracy of handheld data-collection devices, and show that stereo localization clearly outperforms monocular alternatives. Policies trained on data collected with OpenJaws have been deployed on real robots across multiple tasks, and the hardware, software, and data are released under a commercially friendly license.

  2. arXiv cs.RO71

    REACH: An RL-based hierarchical humanoid crawling framework for confined-space traversal

    REACH is an RL-based hierarchical framework that enables a Unitree G1 humanoid robot to traverse height-constrained environments through variable-height bipedal walking and crawling. Its policies regulate body height over complementary command ranges: 1.27–0.50m for bipedal walking and 0.50–0.20m for crawling, and a bidirectional transition policy connects crouched walking and crawling. The framework also combines a LiDAR planner that converts point clouds into collision-free three-dimensional paths and locomotion commands. Real-world experiments validated height and speed tracking, terrain traversal, mode switching, and confined-space traversal; the code and videos have been released.

  3. arXiv cs.RO64

    CARD: A Contact-Anchored Retargeting Framework for Dexterous Manipulation

    CARD is a simulator- and object-model-free framework that retargets human demonstrations into robot actions by explicitly preserving contact force targets, and it handles video, motion capture, and tactile glove data in a unified way. On video, glove, and motion-capture data and the GRAB dataset, CARD maintains contact on 43%–78% of contact frames, whereas purely kinematic and object-aware retargeting methods stay below 10% and 22.5%, respectively.

  4. arXiv cs.RO58

    MyoAcross: A Generalist Muscle-Driven Control Policy for Musculoskeletal Models Across Individuals

    The study proposes the MyoAcross framework, which combines individual musculoskeletal model construction, morphology-conditioned policy learning, and virtual model augmentation to achieve muscle-driven reference-motion tracking without per-individual fine-tuning. Across 31 held-out individual models, it achieved a 99.24% completion rate and reduced tracking error by 22.60% relative to an unconditioned multilayer perceptron. Policy reuse also extended to 22 held-out individual models constructed from single-image shape estimates, height, and body mass, as well as to a model with unilateral lower-limb shortening after asymmetry augmentation.

  5. arXiv cs.RO69

    RoboAuto: Autonomous Robot Program Search through Multi-Level Physical Understanding

    RoboAuto proposes a robot program search framework that organizes physical understanding at three levels—object, scene, and interaction—to guide LLM agents in generating and revising manipulation programs. The method achieves better performance across five benchmark suites, reaching an 89.1% success rate on short-horizon LIBERO-PRO tasks and averaging more than twice the success rate of ASPIRE on LIBERO-PRO Long and LIBERO-Plus.

  6. arXiv cs.RO67

    SVIn+: An Underwater State Estimation Framework Integrating 3D Sonar, Visual-Inertial, Water Pressure, and DVL

    SVIn+ is a multi-sensor state estimation framework for autonomous underwater vehicles (AUVs). Building on the open-source visual-inertial SLAM system SVIn, it integrates water-pressure and DVL measurements into tightly coupled nonlinear optimization and uses a KISS-ICP decoupled front end to generate relative pose factors, incorporating 3D sonar structural information into the factor graph. The authors conducted field deployments in shipwreck and coral reef scenarios, validating drift suppression and global consistency. The paper was accepted to IROS 2026, and the code and datasets have been released on the project website.

  7. arXiv cs.RO71

    Whole-Body Humanoid Control via Stochastic Motion Tokenization

    This study proposes using a stochastic motion tokenizer to generate concise discrete motion representations that can be fed directly into a whole-body tracking policy to execute dance, fighting, and walking motions on the Unitree G1. At matched capacity, the tokenizer reconstructs Unitree G1 motions better than FSQ and VQ-VAE. In real-robot demonstrations, each generated motion lasted 16.8 seconds, and a 35-second fighting-to-dance sequence was completed.

  8. arXiv cs.RO72

    Rollback: Using World-Model Experience Backtracking to Improve Robot Policies

    Rollback proposes a policy-improvement paradigm in which a world model rewinds to critical decision points, branches to try different actions, and compares the outcomes, distilling counterfactual results into action-level supervision without a separately learned value model. On three real-world tasks—block extraction, ball throwing, and tabletop curling—success rates improved by 10.67%, 11.11%, and 11.85% in absolute terms over the strongest baseline, and ball throwing and tabletop curling surpassed the average human player success rate within 8 hours of training.

  10. HuggingFace Daily Papers65

    JAM: A Unified Action Model Framework Decoupling Backbone, Objective, and Inference Mechanism

    The study proposes the Just Action Model (JAM) framework, which breaks down the differences between VLA and WAM into three separable choices: backbone initialization, the future-observation objective, and whether that loss mechanism is retained at inference. It uses a pretrained visual backbone plus an action expert, trained with an action loss and a foresight loss.

  12. OFweek Robotics58

    Jinkong Technology completes tens of millions of yuan angel round, plans to validate core components for space robots by year-end

    Shanghai Jinkong Technology announced on October 26 that it has completed an angel round of tens of millions of yuan, led by CDH VGC, with Shanghai Jiao Tong University Hanyuan Assets, Guoke Green Fund, and Lingqiao Intelligent participating. The funds will be used for R&D of core components for space robots, in-orbit validation, and product engineering.

  15. Reddit r/robotics30

    Training Franka Panda to complete pick-and-place with PPO in PyBullet

    A simulated Franka Panda learns in PyBullet to pick up blocks and place them on a target pad using PPO from Stable-Baselines3; the project aims to understand PyBullet and the full reinforcement-learning robot training pipeline. Future plans include adding text or voice prompts so users can choose which block to pick up and where to place it; the code has been released on GitHub.

  16. The Humanoid Hub75

    Google DeepMind releases Genie 4 world model, capable of generating robot training environments

    Google DeepMind has released Genie 4, a real-time photorealistic world model that can be controlled with natural language, adding native audio and improved physics such as collisions and aerodynamics. The model can generate infinitely variable, controllable training environments for robots and agents, and has been paired with Gemini 4 Argon and Gemini Robotics to have Apptronik's Apollo humanoid robot complete a checkers task step by step in simulation.

  18. Shanghai AI Laboratory - Embodied Intelligence60

    Shanghai AI Laboratory and partners jointly launch materials multimodal large model "Caihua·MatVerse"

    Suzhou National Laboratory, Shanghai AI Laboratory, Shanghai Jiao Tong University and others jointly launched the "Caihua·MatVerse" materials multimodal large model and agent application system, which uses an "independent encoders plus unified decoder" architecture to align XRD spectra, electron microscope images and molecular structures into the same semantic space.

    Why it matters: The materials present a multimodal unified representation architecture and 19-category disciplinary evaluation benchmarks, offering insight into how materials large models can move from retrieval to mechanistic reasoning.

Oct 27Tue
  1. Robotics 24/747

    Intel and SAP demonstrate physical AI and autonomous warehouse deployment

    Intel and SAP have collaborated to connect enterprise IT systems with the operational technology that controls physical devices, and demonstrated physical AI automating warehouse material handling through a proof of concept (PoC). In this PoC, business requests from SAP EWM are sent to autonomous robots equipped with Intel edge AI software and hardware; the robots transport materials and report task status back, forming a closed loop between enterprise workflows and physical execution. The demonstration reduced transport distances and repetitive manual handling.

  2. 机器人全球资讯 · 微信公众号52

    HUMXN subsidizes home repairs in three US cities to train robots with technician footage

    AI company HUMXN has launched a repair cost subsidy program in Minneapolis, Chicago, and Miami, where residents allow technicians to wear recording devices to capture plumbing, electrical, HVAC, duct cleaning, and carpet cleaning work; the footage is used to train AI and robotic systems. Participating technicians use wearable capture devices to record site inspections, tool selection, and troubleshooting, and the processed data is licensed to AI and robotics research organizations. The company says identifying information in the footage is blurred or removed, and services are scheduled only after resident consent.

  3. 甲子光年 · 微信公众号60

    Force Infinite's Chen Jiayu: General large models will eat up task planning—where should robot brains go?

    In an interview with Jiazi Guangnian, Force Infinite chief scientist Chen Jiayu judged that general large models such as GPT-6 Astra will completely eat up the task planning (Planner) portion, so the team will no longer continue investing in some high-level memory mechanism research and will instead focus on execution capabilities in the physical world.

  4. 机器人产业应用 · 微信公众号38

    Embodied AI data workshop held in Suzhou: views from frontline decision-makers on models, data, and real-world deployment

    On October 26, 2026, Robot Industry Application held a closed-door embodied AI data workshop in Suzhou Industrial Park, with more than 20 frontline decision-makers from models, data, real-world deployment, and chip infrastructure participating. Data vendors believe demand for embodied data is far from saturated, but model vendors argued that startups cannot scale data indefinitely; those on the deployment side emphasized cost reduction, efficiency gains, and the logic of calculating returns, and discussed mass production and standardization of tactile electronic skin.

  5. 机器人产业应用 · 微信公众号50

    Qingyan Precision launches automotive-grade Tsing-Ego PRO first-person data collection solution, opens pre-orders

    Qingyan Precision officially launched its automotive-grade Tsing-Ego PRO first-person data collection solution during SAECCE 2026, with pre-orders opening at the same time. The solution integrates synchronized multi-view capture, automotive-grade reliability, lightweight wearability, and on-device quality inspection, serving as the data collection tool for its first-of-its-kind RIL (robot-in-the-loop) pilot testing system to provide high-quality data for robot training, validation, and on-site applications. The industrial-grade Tsing-Glove imperceptible data collection glove will launch soon, and the first batch of partner customers can enjoy priority pilot testing, scenario workstation adaptation, and order matching benefits.

  6. Union Square Ventures · X71

    USV and Creandum co-lead $40 million seed round for Machenta

    USV announced that it co-led Machenta's $40 million seed round with Creandum, as the company also emerged from stealth. Machenta says its robotics foundation model is trained entirely in simulation, with no real-world data, and can learn a task from a single demonstration without additional training, adapting when the environment changes.

    Why it matters: USV, as co-lead investor, explains why Machenta's one-demonstration learning is worth betting on, giving readers insight into the technical claims behind the funding.

  7. 高工咨询 · 微信公众号58

    Sightbit Robotics launches dual-robot collaborative welding workstation and Kunwu industrial simulation platform

    At the 2026 China Marine Economy Expo, Sightbit Robotics showcased a dual-robot collaborative welding workstation for shipbuilding, a humanoid welding robot prototype, an intelligent residual-material scanning system, a steel plate pitting 3D inspection system, and the Kunwu industrial simulation platform. The SpeedWeld intelligent welding control system supports reverse modeling with 3D structured-light cameras to generate welding trajectories, and can reduce changeover and commissioning cycles by up to 90%. The latest SpeedWeld 2.9 version supports dual-robot collaborative, asynchronous welding, and independent welding modes.

  8. 硅星人Pro · 微信公众号22

    Manycore, Meshy, and Hyper3D Discuss AI 3D: Why Chinese Companies Are Leading

    Manycore Tech, Meshy, and Hyper3D discussed why Chinese AI 3D companies are leading at the ACC 2026 AI Creator Carnival. Manycore has launched the spatial generation model SpatialGen and is exploring the 3D generation model Aholo Lux3D, whose materials support up to nine channels; Hyper3D launched Agentic Mode, moving from Production Ready toward Agent Ready. The three companies believe that domestic high-quality 3D data, the production pipeline ecosystem, and talent accumulation are the main advantages.

  10. 机器之心 · 微信公众号76

    Ropedia Releases Six Research Results, Exploring How First-Person Human Data Can Be Turned into Robot Capabilities

    Ropedia released six studies at the first Ropedia Super Week, held October 19 to 23, centered on how first-person human video can be turned into training and execution information usable by robots.

    Why it matters: The six studies collectively address how first-person human data can be converted into training and execution information usable by robots, and present cross-embodiment and real-robot comparison results.

  11. 量子位72

    RoboParty releases full-stack open-source humanoid robot RP1, opening mechanical drawings and motion algorithms

    RoboParty has released the full-stack open-source humanoid robot RP1, opening the entire chain to developers, from mechanical drawings and electrical systems to its self-developed ROMOMO joints, low-level control, simulation training, and deployment. RP1 is 135 cm tall, with 24 active degrees of freedom in the open-source version and 30 in the Pro version; peak torque ranges from 25 to 160 N·m. It uses 48V power and CAN-FD communication, and its accompanying software provides a 500 Hz control frequency and a 50 Hz policy update frequency.

  12. Xbotics具身智能实验室 · 微信公众号75

    Tsinghua team proposes SimpleTouch: fine manipulation learned from 50 demonstrations without tactile policy pretraining

    A Tsinghua University research team proposes SimpleTouch, which adds a tactile expert to the pretrained VLA π0.5 and uses single-stage training with only 50 demonstrations per task, without additional tactile policy pretraining or a separate alignment stage.

  13. 量子位65

    Hesai's Kosmo spatial scanning terminal adopted by Pixar, can output 3DGS data

    Hesai Technology's spatial scanning solution Kosmo has been included by Pixar in a 3D rendering tutorial, where it is used to capture 3D Gaussian splatting data of real-world scenes. Kosmo consists of the handheld capture device Kosmo One and the cloud reconstruction component Kosmo World. Kosmo One integrates a custom lidar, an imaging system of up to 8K, a one-inch CMOS sensor, and a high-precision IMU; the four types of sensors perform microsecond-level time synchronization and factory extrinsic calibration at the hardware layer.

  14. HuggingFace Daily Papers62

    EmbodiedLab releases embodied agent benchmark: robots must acquire knowledge by operating experimental apparatus

    EmbodiedLab is a benchmark that requires robots to "acquire knowledge through action," covering 30 quantitative science experiments across 5 disciplines on 14 apparatus platforms. The parameters of each instance are resampled, so results cannot be known in advance but can be scored precisely.

  15. Automated Warehouse42

    Intel and SAP showcase physical AI and autonomous warehouse deployment in practice

    Intel and SAP have collaborated to connect enterprise IT systems with warehouse operational technology (OT), and used a proof of concept (PoC) to demonstrate physical AI autonomously performing material handling. Requests initiated in SAP EWM are dispatched to autonomous robots equipped with Intel edge AI software and hardware; the robots transport materials and send task status and completion back, forming a closed loop between enterprise workflows and physical execution. The PoC showed reduced transport distances and less repetitive manual handling, and the two parties plan to turn it into a blueprint that can be replicated across sites, robot vendors, and use cases.

  16. Kinetix AI · YouTube67

    Kinetix AI releases KAI World Model, supporting locomotion and manipulation tasks

    Kinetix AI has released the KAI World Model, which is based on parallel video generation and 4D spatial modeling and can simultaneously generate virtual worlds and reconstruct spatial scenes. The model was pre-trained on millions of videos and supports pure locomotion, pure manipulation, and coordinated locomotion-manipulation tasks; it claims generalization across tasks and across robot embodiments. Live demonstrations include a robotic arm autonomously opening a beverage can and a humanoid robot playing real-time table tennis rallies.

    Why it matters: The original shows live demonstrations of the world model on two types of tasks—a robotic arm opening a can and a humanoid playing table tennis—which can be used to understand its approach to generalization across tasks and embodiments.

  17. 量子位58

    Xiaomi unveils 21-DoF biomimetic dexterous hand, validated on 1,827 factory SOPs

    Xiaomi has disclosed its exploration results for a biomimetic dexterous hand, designing a new 21-DoF biomimetic dexterous hand based on the collection and analysis of 1,827 standard operating procedures (SOPs) at Xiaomi's automobile factory. Simulation ablation analysis showed that in the 17–21 DoF range, the average stable grasp success rate improved by 15%–38% compared with 6–15 DoF, while the improvement slowed markedly at 23 DoF and above. The hand uses a hybrid actuation and tendon tension control scheme, with systematic optimization of the heat dissipation system and full-palm tactile sensing.

  18. Beijing Humanoid Robot Innovation Center58

    Beijing Humanoid's open-source RoboMIND dataset surpasses 50 million downloads

    The Beijing Humanoid Robot Innovation Center announced that global cumulative downloads of its open-source RoboMIND dataset have surpassed 50 million, with the most recent 10 million taking only 18 days. The open-source dataset releases more than 400,000 dual-arm manipulation trajectories covering over 700 real-world tasks, supporting dual-arm coordination, mobile manipulation, dexterous hands, and tactile perception. Its data base covers nearly 6,000 square meters and can produce up to 180,000 hours of data per year, and has delivered nearly 30,000 hours of high-quality data externally.

  19. 雷科技70

    AgiBot releases embodied Agent framework Genie Master, validating Physical RSI in a real convenience store scenario

    AgiBot released the embodied Agent framework Genie Master on October 27, enabling robots to autonomously identify the causes of failures after deployment, adjust strategies, and accumulate experience. The framework uses the Embodied Execution Protocol (EEP) to unify four types of interfaces: capability, guidance, feedback, and continuity, and through the two routes of Harness RSI and Policy RSI, it retains experience in prompts and memory, and in action policy parameters, respectively.

  22. arXiv cs.RO72

    JRDB-AVR: An Active Visual Reasoning Benchmark for Embodied Agents in Real-World Environments

    The authors propose JRDB-AVR, an active visual reasoning benchmark built on real JRDB robotics data: after receiving a visual reasoning question, an embodied agent must request limited observations by timestamp and viewing angle, and evaluation examines both the final answer and the visual evidence supporting it.