Technology areas
Data and simulation
Demonstration, teleoperation for data collection, motion retargeting, robot datasets, data quality, physics simulation, synthetic data, digital twins, domain randomization, and sim-to-real transfer. The focus is data, environments, and tools for training and validation. Simulation used only to validate a new learning algorithm does not automatically qualify.
136 selected · 91 in the last 30 days
GitHub Robotics Topic ·
MuJoCo 3.16.0 released: adds compile-time frame scaling, Bazel build, and multiple breaking API changes
MuJoCo 3.16.0 was released on October 14, 2026. Frames gain scale, scaling, and massscale attributes that can scale their contents at compile time without modifying mjSpec. New savecompiled and savecanonical compile attributes preserve the original modeling style, and the core library, simulate, plugins, and examples can now be built with Bazel.
Pollen Robotics · YouTube ·
Pollen Robotics launches Microduck Arena virtual competition arena
Pollen Robotics has released Microduck Arena, a virtual arena where Microduck robots race, train, and compete without the need for physical robots. Users train policies with reinforcement learning and publish them to their own Hugging Face accounts to enter challenges; each submission is evaluated uniformly by the Arena, and results can be compared across players. Published policies can be downloaded as .onnx files to watch replays and learn from the best runs.
Shanghai AI Laboratory - Embodied Intelligence ·
Shanghai AI Lab launches Shusheng SCP-Lab experimental equipment access and collaboration protocol
Shanghai AI Lab has launched Shusheng SCP-Lab, an experimental equipment access and collaboration protocol based on the Scientific Context Protocol (SCP), providing research agents with a unified mechanism for device capability discovery, task interaction, and trusted feedback. It has been open-sourced.
PsiBot/灵初智能 ·
Lingchu Intelligence releases Psi-R2.5, using strong Pair Data to solve human-machine data alignment challenges
Lingchu Intelligence has officially released its embodied model Psi-R2.5, which uses a two-tier architecture with a QwenVL3.5-4B high-level planner plus a Wan2.2-IT2V-5B low-level controller, and proposes the strong Pair Data standard. The model reverse-invokes the Psi-W0 world model to generate human demonstration videos backward from real-robot data, enabling mass production of paired data, and supports in-context learning (ICL) for zero-shot generalization to new tasks. It comes with a HIL+RL post-training framework and is claimed to raise task success rates to 99% after a few iterations taking only 1-2 working days, and has already been deployed at customer sites.
Skild AI ·
Skild AI releases physical self-play post-training results; S1 model learns soccer in simulation and transfers to humanoid robots
Skild AI announced that it post-trained its foundation model S1 through physical self-play, letting the policy play against a recent version of itself with scoring as its sole objective. In NVIDIA Isaac Sim, over 140 years of simulated time, it learned skills such as dribbling past opponents, shielding the ball, and tackling, and these skills were successfully transferred to humanoid robots for matches. The authors believe self-play can break through the capability ceiling of pretrained human data, and the next step will be to extend it to everyday tasks such as collaborative manipulation and city-scale navigation.
PsiBot/灵初智能 ·
Psi Robotics Releases Psi-R2.5 Model: Scaling Human Data for Embodied Intelligence with Strong Pair Data
Psi Robotics released the Psi-R25 robot manipulation model. Its core upgrades are improved data quality and data attribute compression: it reviewed and extracted high-quality data from 100,000 hours of data, and used strong pair data to align human data with robot data.
Figure AI ·
Figure AI releases Helix 2.5, achieving zero-shot full-body autonomy in 30 unfamiliar homes
Figure AI released Helix 2.5, which completed three long-horizon full-body behaviors—tidying a living room, folding towels, and making a bed—zero-shot in 30 Bay Area homes where no data had ever been collected, without collecting data or fine-tuning in the evaluation environments.
PKU EPIC Lab ·
FoldNet++: A Large-Scale Synthetic Dataset for Robotic T-Shirt Folding and Unfolding
PKU EPIC Lab has released FoldNet++, a large-scale synthetic dataset for robotic T-shirt folding and unfolding, covering 6 robotic embodiments, 1K T-shirts, 1K environmental assets, and 120K richly annotated demonstrations.
云启资本 ·
Yunqi Podcast Roundtable: Three Embodied AI Founders Discuss World Models, Scaling, and Deployment Bottlenecks
During the World Robot Conference, Yunqi Capital co-hosted a themed roundtable with SEE Fund, which was included in the podcast Attent!on. Three founders—Xu Huazhe of PokeBot, Li Qiang of Quantum Dynamics, and Liu Nianqiu of Feimo Yi Technology—shared their views on world models, scaling, and deployment.
PKU EPIC Lab ·
GIF: An agentic generation framework for interactive and functional object compositions for robot learning
PKU EPIC Lab proposes GIF, an agentic generation framework for robot learning that reframes the problem as disentangled reconstruction followed by relative pose recovery. CoGen combines 2D and 3D generative models to produce instance-disentangled meshes and coarse initial poses; GPRM refines the relative poses under joint geometric and physical guidance; and a VLM verifier selects the candidate that best matches the structured specification.
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.
自变量机器人 · 微信公众号 ·
X Square Robot releases TwinDEX: a three-finger, nine-DOF dexterous hand trained on purely embodiment-free data
X Square Robot releases TwinDEX, a pair of twin three-finger, nine-degree-of-freedom dexterous hands: one is wearable for data collection, and one is mounted on a robot for real-machine deployment, enabling dexterous manipulation driven purely by embodiment-free data with zero real-machine teleoperation data.
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.
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.
智源研究院 · 微信公众号 ·
BAAI releases FlagEval-Robo embodied intelligence evaluation system and dual leaderboards
BAAI released the FlagEval-Robo embodied intelligence evaluation system on August 21, launching the FlagEval-Robo-Sim and FlagEval-Robo-Real leaderboards and publishing evaluation results for 12 open-source models. All models underwent equal post-training on the evaluation dataset.
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.
PKU EPIC Lab ·
PKU EPIC Lab releases HumanTracker humanoid motion tracking benchmark and HumanScore metric
PKU EPIC Lab proposed the HumanTracker benchmark for evaluating humanoid motion tracking, accepted to ECCV 2026. The benchmark contains approximately 153 hours of optical motion trajectories from multiple professional performers, organized into four motion families with text labels; the accompanying HumanScore metric is trained on 12K motion pairs containing 24K motions, aligns with human preferences, and can reveal contact and stability failures that kinematic metrics often miss, such as foot skating and mistimed landings.
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.