warehouse
At least 11 killed in Ukraine as Moscow and Kyiv continue to trade attacks
Is the war entering a new phase? At least 11 people have been killed in Russian attacks on Ukraine, while Ukrainian attacks on Russia's Kirov region killed six others, officials on both sides of the conflict said. A Russian missile attack killed six people and wounded "dozens" in the Kyiv region on Friday, Ukrainian President Volodymyr Zelenskyy said. Earlier, Kyiv mayor Vitali Klitschko reported explosions in the city and called on residents to stay in shelters as air defence systems were operating. Separately, Vadym Filashkin, the governor of the city of Sloviansk, said five people were killed and nine others injured after Moscow dropped two aviation bombs on the city.
Russia's businesses under strain from Ukraine's attacks on Wildberries
Ukrainian drones have hit several retail warehouses belonging to Russia's biggest online retailer, Wildberries, in a matter of days, dealing a blow to a large number of small and medium-sized businesses. After months of drone attacks on oil depots and refineries, Kyiv says it is now targeting logistics hubs used by Russians to buy military equipment, and disrupting supplies to the Russian army. But it has also frustrated hundreds of Russian sellers who depend on online marketplaces for their livelihoods, making the war feel closer to home after almost four and a half years. I am a mother of a disabled child, I've built the business myself, one woman complained on an expletive-laden social media post that went viral. I've lost 1m roubles (£9,500; $12,700)... We're already getting screwed over from every direction as it is.
Ukrainian drones hit Russian online retailer Wildberries, media and governor say
Ukrainian drones have hit warehouses belonging to Russia's biggest online retailer again, injuring 10 people, according to Russian media and the region's governor. Logistics hubs belonging to Wildberries in Krasnodar and Stavropol were struck during overnight strikes, forcing workers to be evacuated, the company's owner said. It is the second time Ukraine has attacked the firm's facilities in four days, with warehouses in Tambov and Elektrostal hit on Saturday, killing eight and injuring 62. Kyiv has claimed the warehouses have been used to supply components to make Russia's drones and navigation equipment. Wildberries owner Tatyana Kim said on Telegram that there are no words to describe all the feelings and emotions caused by the attacks on ordinary people, on our employees, on us, who are simply doing our jobs. But these situations demonstrate the most important thing: we must continue to do what we do for the benefit of people.
Warehouse robots move packages without human handoff
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Existing Embodied Question Answering (EQA) benchmarks primarily focus on household environments, often overlooking safety-critical aspects and reasoning processes pertinent to industrial settings. This drawback limits the evaluation of agent readiness for real-world industrial applications. To bridge this, we introduce IndustryEQA, the first benchmark dedicated to evaluating embodied agent capabilities within safety-critical warehouse scenarios. Built upon the NVIDIA Isaac Sim platform, IndustryEQA provides high-fidelity episodic memory videos featuring diverse industrial assets, dynamic human agents, and carefully designed hazardous situations inspired by real-world safety guidelines. The benchmark includes rich annotations covering six categories: equipment safety, human safety, object recognition, attribute recognition, temporal understanding, and spatial understanding. Besides, it also provides extra reasoning evaluation based on these categories. Specifically, it comprises 971 question-answer pairs generated from small warehouse and 373 pairs from large ones, incorporating scenarios with and without human. We further propose a comprehensive evaluation framework, including various baseline models, to assess their general perception and reasoning abilities in industrial environments. IndustryEQA aims to steer EQA research towards developing more robust, safety-aware, and practically applicable embodied agents for complex industrial environments.
ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks
Zhang, Zhizhen, Gu, Hyemin, Zhang, Benjamin J., Elenius, Daniel, Tyrrell, Michael, Bourdais, Theo J., Owhadi, Houman, Katsoulakis, Markos A., Sahai, Tuhin
Open time-series forecasting (TSF) benchmarks cover retail, energy, weather, and traffic, but supply-chain logistics remains underserved. We introduce ISOMORPH, the first public digital twin of a multi-echelon logistics network with fully interpretable, user-configurable parameters and modular topology, demand process, and control rules. The simulator advances a directed routing graph in discrete time: demand arrives at the destination, is served from stock or recorded as backlog, and triggers replenishment through the network. The state vector tracks per-node on-hand inventory with outstanding orders, in-transit shipments, and a smoothed demand estimate, so the dynamics close as a Markov chain on a tractable state space whose transition kernel acts linearly on the empirical distribution of the state. The released data reproduces the bullwhip effect at empirically consistent magnitudes, and three conservation laws encoded in the Markov chain serve as verification tools when users extend the simulator. We release datasets at two catalogue scales ($C=50$ and $C=200$) with six scenario sweeps producing 30 additional rollouts and 20 Latin-hypercube perturbations, exhibiting dynamics absent from fixed TSF benchmarks: variance amplification, cascading bottlenecks, regime shifts, and cross-channel coupling through shared macro shocks. Zero-shot evaluation of four foundation models (Chronos, Moirai, TimesFM, Lag-Llama) shows MASE values exceeding public GIFT-Eval references at low-to-moderate horizons, supporting incorporation into existing benchmarks. The same pairing produces forecast confidence bands via Latin-hypercube perturbation of demand-side knobs, forward UQ from parameter uncertainty unavailable on standard TSF datasets, demonstrating that foundation models can serve as fast surrogates for the digital twin's forward UQ. Code (MIT): https://github.com/tuhinsahai/ISOMORPH.
AI system learns to keep warehouse robot traffic running smoothly
Inside a giant autonomous warehouse, hundreds of robots dart down aisles as they collect and distribute items to fulfill a steady stream of customer orders. In this busy environment, even small traffic jams or minor collisions can snowball into massive slowdowns. To avoid such an avalanche of inefficiencies, researchers from MIT and the tech firm Symbotic developed a new method that automatically keeps a fleet of robots moving smoothly. Their method learns which robots should go first at each moment, based on how congestion is forming, and adapts to prioritize robots that are about to get stuck. In this way, the system can reroute robots in advance to avoid bottlenecks.
Inside China's robotics revolution
An engineer at the AgiBot factory in Shanghai, China, where the 5,000th mass-produced humanoid robot had rolled off the production line. An engineer at the AgiBot factory in Shanghai, China, where the 5,000th mass-produced humanoid robot had rolled off the production line. How close are we to the sci-fi vision of autonomous humanoid robots? C hen Liang, the founder of Guchi Robotics, an automation company headquartered in Shanghai, is a tall, heavy-set man in his mid-40s with square-rimmed glasses. His everyday manner is calm and understated, but when he is in his element - up close with the technology he builds, or in business meetings discussing the imminent replacement of human workers by robots - he wears an exuberant smile that brings to mind an intern on his first day at his dream job. Guchi makes the machines that install wheels, dashboards and windows for many of the top Chinese car brands, including BYD and Nio. He took the name from the Chinese word, "steadfast intelligence", though the fact that it sounded like an Italian luxury brand was not entirely unwelcome. For the better part of two decades, Chen has tried to solve what, to him, is an engineering problem: how to eliminate - or, in his view, liberate - as many workers in car factories as technologically possible. Late last year, I visited him at Guchi headquarters on the western outskirts of Shanghai. Next to the head office are several warehouses where Guchi's engineers tinker with robots to fit the specifications of their customers. Chen, an engineer by training, founded Guchi in 2019 with the aim of tackling the hardest automation task in the car factory: "final assembly", the last leg of production, when all the composite pieces - the dashboard, windows, wheels and seat cushions - come together. At present, his robots can mount wheels, dashboards and windows on to a car without any human intervention, but 80% of the final assembly, he estimates, has yet to be automated. That is what Chen has set his sights on. As in much of the world, AI has become part of everyday life in China . But what most excites Chinese politicians and industrialists are the strides being made in the field of robotics, which, when combined with advances in AI, could revolutionise the world of work.
Meet Scotland's Whisky-Sniffing Robot Dog
Inside Dewar's cavernous whisky warehouses, man's best mechanical friend--a Boston Dynamics robot dog with an ethanol sensor for a nose--is on the hunt for leaky barrels. Wooden barrels are what make the magic happen in your favorite bottle of whisky . At Bacardi Limited, the world's largest privately held spirits company, barrel leakage is a massive headache. Consider the company's Dewar's blended Scotch whisky brand (just one of the dozens it owns). Most of the time, Dewar's will have over 100 warehouses full of aging barrels of whisky, 25,000 casks in each one.