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Oct 29Thu
  1. 奥比中光58

    Orbbec and Daxiao Robotics sign 10,000-unit strategic procurement agreement

    Orbbec has signed a 10,000-unit strategic procurement agreement and reached comprehensive strategic cooperation with embodied intelligence company Daxiao Robotics. Orbbec will supply depth cameras, RGB cameras, and bodyless data collection hardware, along with supporting software adaptation and large-scale manufacturing and delivery. The equipment is used in Daxiao Robotics' robot bodies and environmental data collection system, supporting multi-view real-interaction data collection and providing a data source for embodied intelligence model training. The two parties have now entered the product delivery stage.

  2. 钛媒体48

    Unitree shares rebound over 70% in 12 days as GPT-6 Astra fuels embodied intelligence narrative

    Unitree Technology's share price has rebounded by more than 70% over 12 days, with total market value recovering to over 280 billion yuan. JPMorgan raised its target price from 300 yuan per share to 995 yuan per share. Its first post-IPO financial report, released after market close on October 28, showed Q3 revenue of 665 million yuan, up 69.93% year on year, but non-GAAP net profit of 105 million yuan, down 17.42% year on year, and R&D investment of 127 million yuan, up 249.58% year on year.

  3. Fudan Multimodal Embodied Intelligence12

    Seven doctoral students from Fudan University's School of Intelligent Robotics and Advanced Manufacturing Innovation selected for the 2026 CAST Young Science and Technology Talent Cultivation Project Doctoral Program

    Seven doctoral students from Fudan University's School of Intelligent Robotics and Advanced Manufacturing Innovation—Pan Qiqi, Jia Chen, Zheng Boyang, Tao Zijian, Miao Wenqing, Guo Zigu, and Wang Siqi—were selected for the 2026 CAST Young Science and Technology Talent Cultivation Project Doctoral Program. The selected students' research covers areas including surgical robot configuration design and continuum path planning, haptic feedback and mechanical metamaterials, aerospace structural reliability analysis, healthy lighting and lighting human factors engineering, and human factors engineering as well as computational mechanics and artificial intelligence.

  4. Reddit r/robotics22

    Xynova compares 20 dexterous hands in KaRMA simulation; Prima 1 ranks 2nd in translation and 1st in reorientation

    The Xynova team used the KaRMA simulation to compare 20 dexterous hand models; under the test conditions, its Prima 1 ranked 2nd in the translation category and 1st in the reorientation category. The team says a gap remains between simulation and real-world operation and is seeking more practical dexterity metrics. Xynova will attend CoRL in Austin and Web Summit in Lisbon with dexterous hand demonstrations and has spare tickets for people willing to produce technical content for its dexterous hands.

  5. 锐曼REEMAN30

    How Does REEMAN Use the Big Dog Chassis Mobile Platform to Automate Warehouse Shelf Picking?

    REEMAN ROBOT partnered with a German industrial technology customer to develop a mobile manipulator robot for warehouse shelf picking and material handling. The solution uses the Big Dog Chassis AMR platform with a rated payload of 100 kg, paired with a 7-DOF robotic arm with a rated payload of 5 kg and a working reach of 610 mm, as well as a vertical lifting mechanism with a stroke of 1,200 mm.

  6. 锐曼REEMAN25

    Why Are Wheeled Robot Bases Better Suited for Mobile Manipulators? — The REEMAN Big Dog Base as an Example

    The REEMAN Big Dog wheeled AMR base is designed for mobile manipulator integration, with a rated payload of 100 kg, laser SLAM navigation, LiDAR and dual 3D cameras, and HTTP API, Android SDK, RS232, and local MQTT interfaces. Two cases show a customer integrating dual arms on the Big Dog base for a tote-handling demo, and a German industrial customer combining the base with a 7-DOF robotic arm and a 1,200 mm vertical lift mechanism for warehouse shelf picking.

  7. Reddit r/robotics8

    What data does a robot learning project need, and how is it obtained? A student's survey on data collection and evaluation

    A student is seeking experience from practitioners of robot learning projects: what their recent project tasks were, and whether training and testing require human videos, robot demonstrations with action recordings, or sensor data. What camera viewpoints, synchronized recording, annotations, or file formats the data needs to include; whether existing datasets are sufficient or self-collection is necessary; and how to work around insufficient data.

  8. Reddit r/robotics58

    Implementing IMU and image-synchronized visual-inertial odometry with the OpenMV AE3

    The author used a Python script and modified firmware to synchronize the OpenMV AE3 camera's exposure with specific IMU measurements, aiming to improve visual-inertial odometry. The firmware change adds a shared clock between the two CPU cores; the IMU runs at 208 Hz, and every 10 IMU measurements trigger one camera exposure, at about 20 FPS. The code is open-sourced, and test videos of Kimera-VIO in 3 m/s outdoor flight and indoor flight are provided.

  9. OFweek Robotics60

    After a Capital Surge and Deployment Milestones, AGIBOT's Real Test as an Embodied AI Chain Leader Is Just Beginning

    The article reviews AGIBOT's moves in recent months: it publicly introduced a nine-person core partner lineup, launched a Hong Kong IPO, and after completing a new funding round reached a valuation of 50 billion yuan. It also took a controlling stake in SWANCOR Advanced Materials for about 2.1 billion yuan, while spinning off subsidiaries including Mifeng, Critical Point, Qingtianzu, AGIBOT KuoTuo, Zhiding, and Yuansheng Wotu, which was established in October.

  10. OFweek Robotics58

    Unitree Technology Q3 net profit 113 million yuan, down 49.55% quarter-on-quarter

    Unitree Technology's revenue in the third quarter of 2026 was 665 million yuan, up 69.93% year-on-year; net profit attributable to shareholders was 113 million yuan, down 17.37% year-on-year and down 49.55% quarter-on-quarter. The company's R&D investment in the third quarter was 127 million yuan, up 249.58% year-on-year, accounting for 19.10% of revenue. The board secretary's office said the decline in net profit was mainly due to increased R&D investment in computing power and large models, and that the impact is controllable over a longer period.

  11. OFweek Robotics58

    Unitree Technology's Q3 revenue rises but profit falls; JPMorgan still raises target price from 300 yuan to 995 yuan

    Unitree Technology's third-quarter operating revenue was 665 million yuan, up 69.93% year on year, while net profit attributable to shareholders was 113 million yuan, down 17.37% year on year, making its first financial report after listing show higher revenue but lower profit. On October 25, JPMorgan raised its target price for Unitree from 300 yuan to 995 yuan, upgraded the rating directly from underweight to overweight, and raised its humanoid robot sales forecasts for 2027 to 2030. The article also notes that cases such as YunShenChu's STAR Market review and Huandong Robot's termination of listing show that listing reviews for robotics companies are tightening, and several second- and third-tier manufacturers have experienced unpaid wages or bankruptcy.

  12. AgiBot75

    AGIBOT Unveils Worken Metrics Framework, AHA3 Hardware Platform, and G2 Max Industrial Robot at 2026 Innovation Day

    At its 2026 Innovation Day, AGIBOT proposed the Worken (effective intelligent working hours) framework, which measures robots' effective output in real environments using three metrics: number of active robots, autonomous working hours, and output efficiency ratio.

    Why it matters: AGIBOT announced its hardware platform, foundation model, operating system, and mass-production model all at once, giving readers a basis to judge its shift from manufacturing scale to measurable output.

  15. Guyuehome40

    DINOv3 features plus vector database: a retraining-free approach for fixed-camera scenarios

    DINOv3 features plus a vector database can achieve retraining-free operation in fixed-camera scenarios. Mechanistically, this works by changing the data rather than the model; in terms of cost, it shortens the cycle and carries no regression risk. The approach has clear boundaries of applicability: fixed viewpoint, a limited number of categories, stable lighting, and available operations and maintenance conditions.

  17. Guyuehome58

    JEPLO: Terrain-Adaptive Gait Control for Quadruped Robots Based on JEPA and LiDAR Perception

    JEPLO proposes a terrain-adaptive gait control method for quadruped robots that aggregates single-LiDAR point clouds into depth observations and predicts the next-beat latent variable in latent space, without reconstructing images. The method is supplemented by teacher-student distillation and distribution regularization; pretrained weights are reproduced in simulation, and principal component analysis of the latent variables clusters clearly by terrain.

  18. Guyuehome62

    Analysis of Inverted-Pendulum Dynamic Balance Control for a Wheel-Legged Quadruped Robot

    The article derives the dynamics of a wheel-legged inverted pendulum and explains why the wheels must accelerate in the direction of the fall for a quadruped robot to stand on only its two rear wheels. It also analyzes the privileged-information design of an asymmetric actor-critic and tests the limits of four policies through cross-physics-engine experiments.

  19. Guyuehome60

    OpenDoge uses observation-history implicit state estimation to control quadruped robot locomotion

    OpenDoge proposes a hybrid internal model for quadruped robot locomotion control that, without terrain maps or contact sensors, encodes observation history into a velocity estimate and a 16-dimensional latent state to determine gait phase and external disturbances. The article combines real inference data to examine what information the latent state carries and what it lacks.

  20. Guyuehome58

    OpenWAM code walkthrough: Dual-System architecture and Flow Matching training pipeline

    Gu Yue Ju published a source-code walkthrough of OpenWAM, covering the project structure, the Dual-System architecture, Video/Action joint attention, the Flow Matching training pipeline, and inference deployment, organized around key code. The material provides only an abstract and does not give specific code details or conclusions.

  21. Guyuehome42

    CKT-WAM source code walkthrough: Teacher intermediate-layer feature extraction and AdapterBank routing

    This CKT-WAM source code walkthrough focuses on Teacher intermediate-layer feature extraction, AdapterBank compression and routing, and the full pipeline for injecting Context into the Student WAM. The article breaks down this information pathway from teacher features to the student world model (WAM) section by section, together with the key code files.

  22. Guyuehome51

    Robomimic Recurrent Behavior Cloning Policy: Likelihood Modeling, LSTM Deployment, and OSC Control Reproduction

    This content describes reproducing the lift and can manipulation tasks in MuJoCo using the official recurrent behavior cloning weights from the robomimic model zoo. It reconstructs the mathematical details of BC likelihood modeling, LSTM deployment semantics, and OSC impedance control.

  23. Guyuehome58

    Deploying the CLIP vision encoder to the RK3588 NPU: notes on export, RKNN conversion, and mixed quantization

    The author documents the full process of deploying the CLIP vision encoder to the RK3588 NPU, covering model export, conversion to RKNN, and mixed quantization, and collects the problems encountered along the way. The material provides only a summary and does not give specific quantization configurations or performance data.

  28. Guyuehome58

    FTNCBF: Fault-Tolerant Neural Control Barrier Functions Under Sensor Failures and Attacks

    FTNCBF addresses the failure of barrier-function safety guarantees when sensors are attacked. It runs estimators in parallel for each fault hypothesis, converts estimation uncertainty into first- and second-order correction terms in the barrier condition, and then synthesizes fault-tolerant control via a minimum-norm program. The method was reproduced in spacecraft and UAV scenarios.

  29. Guyuehome57

    WaterSpiderbot: Kinematic Modeling and Reinforcement Learning Gait Control for an Eight-Legged Bionic Spider Robot

    This material analyzes the eight-legged bionic robot WaterSpiderbot, covering forward and inverse kinematics of the three-joint leg chain, MuJoCo contact support mechanics, and the SAC gait policy, and provides a complete reproducible training loop. The article also diagnoses the structural reason why learning never starts under the default configuration and offers a fix.

  31. Guyuehome58

    Dexterous Hand in Practice 02: Brushless, Coreless, and Servo Motors — How to Choose Joint Motors

    Gu Yue Ju has published the second installment of its Dexterous Hand in Practice series, comparing the trade-offs among brushless motors, coreless motors, and servo motors for dexterous-hand joint selection. Currently only the title and abstract are available; the body text does not provide specific parameters or selection conclusions.

  32. Guyuehome58

    AME: Terrain-attention encoding controls G1 humanoid robot walking on complex terrain

    The article introduces a terrain-attention encoding method called AME that encodes a 1.6×1.0-meter elevation map for the G1 humanoid robot into 187 terrain tokens, uses the robot's proprioceptive state as a single query for cross-attention to extract terrain features, and the policy uses these to walk on steps, plum blossom piles, and slopes. The article derives the encoder structure, attention mechanism, and reward design; the full body of the text is not provided in the materials.

  33. Guyuehome48

    Dexterous Hand in Practice 04: Designing a Single Finger in SolidWorks, Reserving Space for Transmission and Sensing First

    The fourth installment of the Dexterous Hand in Practice series explains how to design a single-finger structure in SolidWorks. The core approach is to reserve mounting space for transmission and sensing components during the modeling stage. The content is aimed at beginners in dexterous hand R&D and is part of the structural modeling step in the design workflow.

  34. Guyuehome58

    Lidar-E2E: End-to-End Obstacle Avoidance Control with Onboard LiDAR for Quadrotors

    Lidar-E2E proposes an end-to-end obstacle avoidance control method for quadrotors using onboard LiDAR. It pools point clouds from a 1944-line LiDAR into a 36×6 range image, concatenates this with a 20-dimensional body state, and directly outputs attitude increments and throttle, which are executed by a low-level PX4 cascaded attitude controller. The article also derives a rotor identification model, the sensing pipeline, and reward shaping, and uses Isaac Sim.

  36. Guyuehome40

    A* and Dijkstra show no measurable difference across 18 runs in Gazebo mecanum-wheel robot simulation

    In a Gazebo mecanum-wheel robot simulation, A* and Dijkstra showed no measurable difference after 18 runs each, and the author wrote "no difference" into the conclusion. The article also discusses how to determine that an experiment showing no measurable difference is not simply the result of a flawed setup.

  37. 锐曼REEMAN29

    How Does a Wheeled Robot Chassis Support Dual-Arm Mobile Manipulation? REEMAN Big Dog Customer Integration Case

    A customer integrated a dual-arm mobile manipulator on the REEMAN Big Dog wheeled AMR chassis; in an 82-second demo, it completed dual-arm grasping of a blue material box, transport between workstations, and placement. The chassis has a rated payload of 100 kg, uses laser SLAM navigation, is equipped with LiDAR and dual 3D cameras for obstacle avoidance, and offers development interfaces including an HTTP API, Android SDK, RS232, and local MQTT. The video is a customer integration demo, not evidence of a production deployment or verified throughput performance.

  38. 钛媒体62

    Unitree Technology 2026 Q3 Report: Revenue 1.817 Billion Yuan, Up 55.71%; Non-Recurring Net Profit Down 18.78%

    Unitree Technology's 2026 Q3 report shows revenue of 1.817 billion yuan for the first three quarters, up 55.71% year on year, and non-recurring net profit attributable to shareholders of 349 million yuan, down 18.78% year on year; net profit attributable to shareholders and non-recurring profit both declined in the third quarter.

  39. OFweek Robotics72

    Tesla starts Optimus mass production in Fremont, California, as Q3 profit falls 43% year over year

    On October 21, Tesla announced the start of mass production of its Optimus humanoid robot at its former electric vehicle plant in Fremont, California, calling these its first mass-production-quality robots; Musk said the target is 20,000 units per week by the end of 2027. Tesla's Q3 revenue was $28.04 billion, roughly flat, while net profit was $787 million, down 43% year over year; the company said profits were mainly consumed by AI projects and Optimus investment. Musk acknowledged that the ramp-up will be slow and bumpy, and that the robot's safety, reliability, and battery life still need work, with a great deal of work remaining on AI capabilities in open scenarios.

  40. 钛媒体22

    Time Is Running Out for Embodied Intelligence

    The embodied intelligence sector has fallen into involution marked by "funding first, demos first, and serving narratives rather than real deployment," with projects that can be stably commercialized accounting for less than 5% of all humanoid robot projects. The article points out that high specifications, high-fidelity simulation, and impressive demo effects have become common problems in humanoid robot projects, with persistently high failure rates, high maintenance costs, and poor robustness in extreme environments, and criticizes that scenario pilot assessments still fall back on single demonstrations and standardized scoring.