NASA announced a series of Moon Base contracts and mission updates, covering commercial robotic cargo delivery, the nuclear-powered rover PROMISE, launch and orbital transfer services, and lunar surface infrastructure.
NEURA Robotics has entered a partnership with E.ON and the enviaM Group to jointly develop Physical AI for critical energy infrastructure, for inspection, asset monitoring, and assistance with high-risk, physically demanding, or repetitive work.
PAL Robotics announced the ARAL project, funded by the EU's EIC, to develop a humanoid robot capable of working in existing warehouses based on the bipedal humanoid research platform KANGAROO, with the first phase aiming to advance from TRL 4 to TRL 5.
From a supplier perspective, REEMAN provides a five-item checklist of mechanical prerequisites, communication architecture, and responsibility division for autonomous forklift and elevator integration. For a single elevator, a local LoRa direct connection to the elevator control module is used; for multiple elevators, MQTT is used with the fleet system queuing and dispatching. The elevator control module only coordinates calls and status and does not replace the elevator's native safety controls. In the Maoming factory case, Ironhide transports about 1,000 kg of wire rod per trip over a one-way distance of about 100 m, completing 65–85 cross-floor elevator tasks per day.
REEMAN autonomous forklifts perform a task-level handshake with turntable stretch wrappers via an external wireless module: the forklift places the pallet and, after retreating from the rotating area, sends a start signal; the wrapper completes rotary film wrapping and automatic film cutting, then returns a completion signal, after which the forklift re-identifies and aligns to pick up the load.
REEMAN automated forklifts integrate with WMS, MES, ERP, and WCS through open APIs and SDKs. Business systems issue transport requests, the fleet scheduler assigns tasks, and the robots execute them using laser SLAM navigation and report completion status back.
Huan'er Technology compares two open-source 6-axis robotic arms that natively support the Hugging Face LeRobot ecosystem: the SO-ARM101 has a 200 g payload, a 400 mm reach, and a maximum servo torque of 30 kg·cm, making it suitable for beginners learning teleoperation and imitation learning; the NexArm has a 500 g payload, a 500 mm reach, and 65 kg·cm torque, features an aviation-grade metal body, and can be expanded with peripherals such as the K230 vision module and a Mecanum-wheel chassis.
Lingchu Intelligence and Hengyan Technology are jointly delivering the Li-Ning East China Smart Logistics Center project. The embodied robot, equipped with Lingchu's self-developed model, has been deployed on site and entered trial operation, taking on routine work and fulfilling commercial orders. The solution targets the bin-picking scenario in footwear and apparel warehousing, where shoeboxes are mixed in storage and item poses are random. The model can autonomously break down multi-step goals and complete recognition, pose estimation, dexterous grasping, product sorting, and pushing full boxes, without requiring large-scale modification of existing infrastructure. During the trial operation, Lingchu will work with Li-Ning's warehouse operations team on stress testing and validation of abnormal conditions, optimizing bin-picking success rates and stability during long periods of continuous operation.
Lingchu Intelligence, together with Beihang University, Peking University, and The Chinese University of Hong Kong, proposed a frequency-aware flow matching method called FAFM; the paper was accepted to the NeurIPS 2026 main conference. The method uses the discrete cosine transform (DCT-II) to represent actions as frequency-domain coefficients corresponding to real time, performs flow matching in coefficient space and constrains the first-order time derivative, requires no additional learnable parameters, and can be used independently or integrated into VLA models such as π₀ and π₀.₅.
Why it matters: The paper presents a frequency-domain action representation that adds no learnable parameters and can be integrated into existing VLA models, offering a transferable approach for joint training on heterogeneous-frequency data.
RoboFFT, proposed by the PKU-Spirit AI Joint Lab, has been accepted to CoRL2026. It is a reinforcement learning post-training method for generative robotic policies that reuses the forward noising process from diffusion model and flow model pretraining to construct an approximate probability ratio for PPO-style clipped updates.
Why it matters: The method reuses the forward noising loss of diffusion and flow models to construct policy update signals, offering a reusable approach for post-training generative policies.
REEMAN autonomous forklifts use laser SLAM navigation and can connect to existing WMS, MES, and ERP systems without magnetic strips or QR codes; the integration focus is on location mapping and open API connectivity rather than rebuilding navigation infrastructure. The guide covers site surveys, map creation, task triggering, and multi-vehicle fleet scaling. Each model is rated for 6 hours of continuous operation (fully loaded)/8 hours (empty), supports automatic return to charging, and some models allow manual battery swapping.
The REEMAN intelligent pallet wrapping and handling workstation uses an external wireless communication module to link the 1.5-ton payload Ironhide autonomous forklift with a turntable wrapping machine into a continuous process. The module can use I/O, RS485, Ethernet, or CAN interfaces depending on the equipment controller, and the wireless link uses LoRa or Wi-Fi. In the demonstration, pickup alignment deviation was ≤2 cm and drop-off deviation was ≤5 cm; wrapping and film cutting are completed automatically, and the full handling and packaging process takes about 6 minutes.
Shao Lin, founder of RoboScience, spoke at the 2026 World Physical AI Conference and Unitree Partner Ecosystem Conference, presenting a cross-embodiment dexterous manipulation technology path from the ICRA 2025 Best Paper D(R,O) Grasp to the T(R,O) Grasp series and then to the FingerEye visuotactile framework.
A team at CMU's Robotics Institute has proposed the Wiggle and Go system, in which a robot first briefly wiggles a rope or cable while an overhead camera records how the waves propagate; a computer vision algorithm then tracks the motion and estimates the object's physical properties, which are used to plan subsequent actions without repeated trial and error. The model is trained entirely in simulation, and properties are then estimated from the motion of real ropes being wiggled to improve prediction accuracy on real hardware. The research has been accepted to the 2026 Conference on Robot Learning (CoRL) and will be presented next month in Austin; it is partly funded by the U.S. National Science Foundation.
Why it matters: The method estimates a rope's physical properties from a single wiggle and then plans actions accordingly, offering a transferable approach to deformable object manipulation.
Daimon Robotics announced the completion of a strategic funding round of hundreds of millions, led by Ant Group with existing shareholders oversubscribing, just two months after its hundred-million-yuan Series A. The company also launched its tactile-anchored world model Daimon-TWM, with parameter scale at the 10B level, capable of real-time inference on the NVIDIA RTX 5090 platform, and claims that its average success rate on contact-intensive manipulation tasks is twice that of π0.5. Daimon has also built the tactile full-modality dataset Daimon-Infinity; after the first 10,000 hours of data were open-sourced, it received nearly 5 million downloads on the ModelScope community.
Why it matters: Beyond the funding news, the original article also details the architecture and data-collection layout of the tactile world model Daimon-TWM, which helps in understanding the technical proposition of the tactile approach.
At IROS 2026, held September 27 to October 1 in Pittsburgh, USA, Daimon Robotics presented its full-chain physical intelligence system spanning perception, data, and models under the theme From Touch to Intelligence, centered on the Daimon-TWM tactile-anchored world model.
PHYMI officially released its first robot, Sagi, on October 28. It adopts a "four-wheeled-legged humanoid configuration" combining four wheeled legs with a humanoid upper body, dual arms, and a rear box, targeting scenarios such as office delivery, community errands, and outdoor camping transport.
Why it matters: The first four-wheeled-legged humanoid robot presents a complete design approach covering configuration trade-offs, a three-layer model, and a data system, allowing comparison with existing bipedal routes to understand the choice of form.
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.
AgiBot has released the embodied foundation model GO-3 Preview, built on its self-developed WRAM (World Reasoning Action Model) architecture that unifies task understanding, future state prediction, and action generation, and it ranks first on three embodied intelligence benchmarks: RoboDojo, RoboTwin, and RoboColiseum. It is planned to be fully open-sourced by the end of 2026.
Why it matters: The original article fully discloses GO-3 Preview's three-stage design of pretraining, post-training, and post-deployment learning, which can be used to understand the engineering path for scaling embodied models across their full lifecycle.
Dexmate provides a teleoperation data collection solution for physical AI model training, consisting of the full-body platform Vega 1 Pro, the half-body platform Vega 1 U, and the Omniteleop software.
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.
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.
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.
AgiBot has released Genie Studio 2.0, an embodied intelligence application platform covering development, deployment, and operations. It consists of three modules—Flywheel, Agent, and Monitor—that connect data collection, model training, evaluation, inference, task orchestration, and robot fleet management.
Why it matters: The original text provides the platform's three major modules and validation data from multiple production lines, which can be used to assess the engineering chain of embodied applications from development to operations.
Two projects led by Zhujing were selected for Jiangsu Province's 2026 high-quality dataset program: the "High-Quality Dataset Construction Project for Embodied Intelligent Robot Logistics Sorting and Handling" was named a key construction project, and the "Embodied Intelligence Atomic Skill Dataset for Office, Catering and Other Scenarios" project was named a cultivation project. Zhujing brought its humanoid robots "Xiaozhu" and "Jingzai" to the exhibition floor of the 2026 Physical AI and World Models Conference. Its embodied intelligence datasets for four scenarios—office, supermarket, catering and housekeeping—have been listed and traded on the Jiangsu Province Data Exchange.
Two projects led by Zhujing were selected for Jiangsu Province's 2026 high-quality dataset program: the "High-Quality Dataset Construction Project for Embodied Intelligent Robot Logistics Sorting and Handling" was named a key construction project, and the "Embodied Intelligence Atomic Skill Dataset for Office, Catering and Other Scenarios" project was named a cultivation project. Zhujing brought its humanoid robots "Xiaozhu" and "Jingzai" to the exhibition floor of the 2026 Physical AI and World Models Conference. Its embodied intelligence datasets for four scenarios—office, supermarket, catering and housekeeping—have been listed and traded on the Jiangsu Province Data Exchange.
Beijing Humanoid launched the "Huisi Kaiwu App Store" in October. Robot skills are packaged as apps that can be searched, downloaded, and deployed with one click to run on full-size general-purpose robots and other bodies. The store also offers datasets and simulation assets, and the official skill app library is open for free; developers who list skills and have them called for a fee can share in the revenue. Users can search for "Jushen Tiangong" in mobile app markets and enter the app store as developers to use the relevant features.
In an exclusive interview with Caixin Time, Xiong Youjun, CEO of the Beijing Humanoid Robot Innovation Center, said the humanoid robot industry has no bubble, only bubble companies, and that the share of prototype robots actually doing real work remains limited. He disclosed that about 80% of Tiangong's data training comes from virtual simulation and 20% from real-world scenarios, that the Pelican-Unify unified representation embodied world model can improve execution accuracy but has high computing power requirements, and that the next funding round is already being planned.
The KAI Halo case study EgoWild2Dex shows how high-quality bimanual dexterous manipulation capabilities can be derived from highly challenging egocentric data. The project page is https://mmlab.hk/egowild2dex.
Why it matters: The material presents a complete training path from first-person human data to robotic bimanual manipulation, along with success rates; its transferable aspect lies in its approach to data utilization.
TUM RoboGym opened in October at the TUM Convergence Center at LabCampus at Munich Airport. It has 48 training units and about 100 robots, and is open to TUM researchers as well as external institutions, universities, and companies.
Why it matters: The original explains how a large-scale real training facility organizes data collection and sharing against the backdrop of scarce real physical interaction data, and can serve as a reference case for embodied intelligence data infrastructure.
NEURA Robotics and the Technical University of Munich (TUM) have opened TUM RoboGym at LabCampus near Munich Airport, covering more than 2,300 square meters. TUM MIRMI is a co-builder, the initial collaboration runs for three years, and the two parties are jointly investing about 17 million euros, of which NEURA is contributing about 11 million euros.
Why it matters: The original text covers both the new robot's hardware changes and the three sources of training data, letting readers understand NEURA's approach of tying data infrastructure to the hardware launch.
At the Industrial World Model session of the 2026 Physical AI and World Models Conference, Tianfu Software made the global debut of its Industrial World Model Generator (IWM Generator), which organizes drawings, engineering models, test data, and operating records into models that can run according to engineering principles.
NVIDIA has expanded the Cosmos platform with new training tools, simulation checkpoints and Cosmos Data Factory blueprints for training, evaluating and deploying world models.
Why it matters: The original lists Cosmos's new training tools, simulation checkpoints and data blueprints, and gives specific data on users such as Porsche and ANYbotics, which can be used to assess changes in the world model development workflow.
NVIDIA announced several implementations of open models and physical intelligence in European retail: Shopify used NVIDIA Megatron Bridge and NeMo RL to post-train Nemotron 3.5 Lightning, cutting serving costs by 90% and delivering 7x faster responses on internal benchmarks.
SEER Robotics demonstrated its robotic arm completing the full coffee-making process without human intervention, from picking up the portafilter, receiving grounds, distributing and tamping the grounds, locking the portafilter, extraction, to cleaning. This is the longest multi-step robotic coffee task the company has demonstrated to date.
At NVIDIA GTC Berlin, Agile Robots partnered with Audi to demonstrate using Dassault Systèmes' DELMIA virtual twin to evaluate how mobile humanoid robots perform in production logistics systems before deployment.
Kinetix AI has launched a first-person human data solution for embodied AI, centered on the lightweight head-worn data capture device KAI Halo. It combines multimodal data collection with edge-cloud AI capabilities to turn real human activity into high-quality training data.
At GTC Berlin, NVIDIA showcased its full lineup of local AI hardware and announced multiple software and ecosystem updates for RTX Spark, DGX Spark, and DGX Station.
At GTC Berlin, NVIDIA announced an expansion of the Isaac open-source robotics development platform, adding the Isaac OS runtime, the officially released Isaac Lab 3.0 learning framework, and an open-source reference workflow based on DGX Station.
Why it matters: The original text lists the runtime, learning framework, and open-source workflow newly added to the Isaac platform, allowing readers to judge the specific changes in the data-to-deployment pipeline.
NVIDIA has opened early access to the Factory Operations Blueprint (FOX) on GitHub, enabling developers to build persistent factory management agents that coordinate robot operations, as well as specialized agents for tasks such as visual inspection and root cause analysis.