Technology areas
Robot models and learning
Robot VLA models, general action and world models, imitation and reinforcement learning, skill and motion policy learning, online adaptation, and transfer across tasks and robot bodies. The contribution is a model, policy, or learning method. Dataset releases belong under Data and simulation; inference deployment belongs under Software and compute systems.
206 selected · 116 in the last 30 days
中科慧灵 · 微信公众号 ·
CASIA and others propose World4RL: diffusion world model combined with reinforcement learning to optimize robot manipulation policies, real-world success rate rises to 93.3%
The Institute of Automation of the Chinese Academy of Sciences, Zhongguancun Academy, and the CASBOT team propose World4RL, a policy optimization framework for robot manipulation that combines a diffusion world model with reinforcement learning, enabling robot policies to be optimized end-to-end in imagined trajectories generated by the model without additional real-robot interaction.
PKU EPIC Lab ·
ZETA: A Controlled Study of Zero-Shot Cross-Embodiment VLA Transfer for Tabletop Manipulation
PKU EPIC Lab published the ZETA study on arXiv (arXiv:2609.02546), proposing a unified definition of zero-shot cross-embodiment VLA transfer and a controlled benchmark covering 14 held-out target embodiments, distinguishing strict zero-shot transfer from pretrain-exposed transfer. Experiments show that local end-effector state-action representations, source embodiment diversity, and auxiliary co-training improve transfer by about 15, 18, and 7 percentage points, respectively, and that adding only 5% target-embodiment data during pretraining raises average target-embodiment progress by 13.4 percentage points.
小鹏机器人 ·
XPeng's second-generation VLA large model gets its first major upgrade, XOS 6.3.0 to debut globally on the G9L
XPeng held a sharing and experience day themed "TIME," announcing the first major upgrade to its second-generation VLA large model. The new XOS 6.3.0 version will make its global debut on the XPeng G9L, with the core aim of moving AI from 3D spatial understanding to 4D spatiotemporal understanding.
Pollen Robotics · YouTube ·
Pollen Robotics opens pre-orders for Microduck, a 25 cm reinforcement learning robot
Pollen Robotics has opened pre-orders for Microduck at $399 (excluding taxes and shipping), with first deliveries targeted before Christmas 2026. The 25 cm-tall robot is built for reinforcement learning, with 15 degrees of freedom, a front camera, an 8x8 LiDAR, two IMUs and a full sensor suite, and supports designing behaviors in simulation and transferring them to the real robot.
Pollen Robotics · YouTube ·
Pollen Robotics launches Microduck, a $399 tiny robot that can be trained in simulation
Pollen Robotics has launched Microduck, a 25 cm tall, 780 g, 15-degree-of-freedom tiny robot, priced at $399 for pre-order (excluding taxes and shipping), with first deliveries targeted before Christmas 2026. It comes in four colorways: Cream, Graphite, Lavender, and Sky.
自变量机器人 · 微信公众号 ·
X Square Robot releases WALL-SS next-scale autoregressive world model
X Square Robot has released WALL-SS, a next-scale autoregressive world model that uses a coarse-to-fine, layer-by-layer refinement generation architecture, breaking away from the traditional diffusion-model approach of generating video in a single segment. In testing, its action-following score was 0.29, the only nonzero score among the compared models; the overlap between generated trajectories and action instructions rose from 0.251 to 0.539; streaming inference can reach 60 seconds of footage without collapse; and in closed-loop policy consistency tests across 6 tasks and 5 training stages, the success-rate agreement between virtual and real-world tasks reached 93%.
PsiBot/灵初智能 ·
Lingchu Intelligence completes over $100 million new funding round, with industrial capital including Tuopu Group and Chery Ruicheng Fund participating
Lingchu Intelligence announced the completion of a new funding round of over $100 million. Investors include Tuopu Group, Ruicheng Fund under Chery Holding, Lens Technology, 37 Interactive Entertainment, Wuhu Municipal Investment Holding Group, and Fosun Chuangfu, while existing shareholder Zhuhai Technology Industry Group made an excess additional investment. The proceeds will focus on embodied world model R&D and commercial deployment in logistics and advanced manufacturing scenarios. The company's self-developed dual-system architecture comprises the Psi-R2 manipulation policy model and the Psi-W0 action-conditioned world model, and it plans to expand the scale of human data collection and accelerate the layout of data collection facilities.
Figure AI ·
Figure AI launches Index app to build large-scale, diverse robot training dataset
Figure AI announced it is exiting stealth mode and launching the Index app on Google Play and the App Store to collect real-world physical data from Creators worldwide to train its Helix AI system.
加速进化 · 微信公众号 ·
Tsinghua's Zhao Mingguo team publishes Science Robotics paper proposing a unified perception-motion reinforcement learning framework for vision-driven humanoid soccer skills
On August 19, Professor Zhao Mingguo's team in Tsinghua University's Department of Automation published the paper "Learning Vision-Driven Reactive Soccer Skills for Humanoid Robots" in Science Robotics, selected for the August 2026 humanoid robotics special issue; the robot platform used was a humanoid robot independently developed by Booster.
Skild AI ·
Skild AI releases robot foundation model S1, achieving in-context learning through video demonstrations
Skild AI released the robot foundation model S1, which uses video demonstrations as task prompts and can execute manipulation tasks not seen during training without fine-tuning, with long-horizon tasks lasting up to about 10 minutes. At a pretraining data scale of 100,000 hours, the ICL model achieved a 66% success rate on unseen tasks, compared with 9% for the language-prompted VLA; a single demonstration was equivalent to about 380 post-training demonstrations, and the planting task took 11 minutes from recording the demonstration to autonomous execution. S1 was trained on NVIDIA AI infrastructure and has already been put into use with commercial partners.
Harbin Institute of Technology Robotics ·
HIT's Wu Zhiguang team develops adaptive magnetically controlled nanorobot swarm platform, achieving navigation in the spinal canal of mice and non-human primates
Professor Wu Zhiguang's team at Harbin Institute of Technology (HIT), together with collaborators, developed an adaptive magnetically controlled nanorobot platform that can form swarm motion patterns such as vortex, chain, and ribbon under external magnetic field drive, and achieved targeted navigation within the spinal canal in mice and non-human primates. The results were published in Science Advances.
Elite Robots/艾利特机器人 ·
Elite Embodied Dual-Arm Robots Enter Apple Supply Chain Drilling Workshop for Mass-Production Loading and Unloading
The embodied dual-arm loading and unloading robot jointly developed by Elite and Maixing Robotics has achieved 24/7 unmanned mass production in the drilling workshop of a leading Apple supply chain factory, with a single-cycle takt time of 52 seconds, a loading and unloading yield of 99.9%, and 5 units stably online. The solution uses hybrid force-position control and dynamic trajectory planning to achieve dual-arm coordination, is equipped with the self-developed Yuanqi Primo embodied large model, achieves loading accuracy within ±0.2 mm, and uses a wireless IO four-step handshake scheme to eliminate the need for modifications by the original machine tool manufacturer, shortening the deployment period from 10 days for the first unit to 7 days for the fifth unit.
艾利特机器人 · 微信公众号 ·
Elite embodied dual-arm robots enter Apple supply chain drilling workshops for mass-production loading and unloading
An embodied dual-arm composite loading and unloading robot jointly developed by Elite and Maixing Robotics has been running in mass production in the drilling workshop of a leading Apple supply chain factory, with a single-cycle takt time of 52 seconds and a loading/unloading yield of 99.9%; the first unit has run continuously for more than a year, and 5 units are online simultaneously.
达纳灵动 · X ·
Dyna Robotics releases Dyna-2 world-action model, pretrained on one million hours of human video
Dyna Robotics introduces Dyna-2, a world-action model pretrained on one million hours of human video. The authors say they found several new scaling laws at this scale: world-action models across four orders of magnitude on human data (from 1,000 hours to 1.
LeadeRobot ·
Mila and Polytechnique Montréal team open-source ~$2,000 robot guide dog Milo, built on Unitree Go2 for autonomous indoor and outdoor navigation
Mila-Quebec AI Institute and a Polytechnique Montréal team have released Milo, an open-source robot guide dog that they say can cut the roughly $50,000 cost of a guide dog to about $2,000. The hardware base is a Unitree Go2 Air/Pro plus an NVIDIA Jetson Orin Nano; a magnetic-encoder telescoping handle is used to inversely solve the user's 3D position, a bird's-eye-view map is built first and then a navigation policy is run, and the policy is trained in about 10 minutes in GPU-accelerated simulation and deployed zero-shot on the real robot.
LeadeRobot ·
Italy's IIT and INAIL unveil ergoCub humanoid robot; human-robot collaborative lifting can reduce load on the human lumbosacral joint
The Italian Institute of Technology (IIT) and INAIL proposed a shared embodied intelligence architecture and built the humanoid robot ergoCub; the research was published in Nature Machine Intelligence.
RoboParty · 微信公众号 ·
RoboParty Lab, Zhejiang University, and Tsinghua AIR release and open-source world model control method INTACT
RoboParty Lab, Zhejiang University, Tsinghua University Institute for AI Industry Research (AIR), and InSpatio jointly released and open-sourced the world model control method INTACT (INtent-To-ACTion).
北京智在无界科技有限公司 ·
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.
Holiday Robotics ·
Holiday Robotics's FlashSAC Paper Wins RSS 2026 Best Paper Award, a First for a Korean Team
A paper by Holiday Robotics researchers won the Best Paper Award at RSS 2026, a first for a Korean team. Its FlashSAC is a reinforcement learning algorithm that shortens humanoid robot walking training from several hours to a few minutes, overcoming the trade-off between learning speed and stability.
Sunday Robotics ·
Sunday Robotics previews ACT-2 model with 99.1% zero-shot success rate in clothes folding
Sunday Robotics previewed its robot model ACT-2, which achieved a 99.1% (±0.3%) zero-shot success rate in clothes folding across diverse unseen home environments with zero per-home adaptation, covering 9 clothing categories across 785 autonomous attempts, with an average folding quality of 4.72/5.