The paper presents HumanVerse-500, a 500-hour dataset of human loco-manipulation behaviors collected with a lightweight wearable system. It introduces λ₀, a whole-body humanoid vision-language-action policy trained through three stages, achieving state-of-the-art performance on real-world tasks and analyzing how human data supports downstream control.
This research presents a recurrent teacher-student framework that learns a single policy in simulation to jointly command flight, arm motion, and gripper closure without explicit task-phase input. The method achieves high success rates in simulation under nominal, physics/control-randomized, and additional camera-randomized conditions.
IndoorBEV is a lightweight LiDAR perception framework that addresses the challenge of efficient indoor perception by integrating height-aware BEV representations and geometry-conditioned feature fusion. It achieves 0.6M parameters, 2.3 MB storage, and 169.6 ms latency on an NVIDIA AGX Orin, with a 1.8% deadline miss ratio.
Sanctuary AI@TheSanctuaryAIEditorial score1515
Professor Shi Qing's team from Beijing Institute of Technology was inspired by the high-speed running mechanism of the elephant shrew. They designed a micro quadruped robot named FLEXOR equipped with a dual-joint coupled spine. Through dynamic spine-leg coordination, the robot achieved a 31.6% increase in speed and a 32.2% reduction in energy consumption without upgrading its motors. The study reveals the critical role of the timing coordination between the spine and legs in locomotion performance and verifies the universality of this mechanism across different robot morphologies, providing new insights for highly mobile embodied intelligent robots.
The Stanford team's HomeBody project demonstrates how GPT-6 Astra controls the Unitree G1 robot to complete kitchen cleaning tasks through a three-step process: spatial exploration, digital twin simulation, and task execution. The system uses pre-trained models and a skill library to perform complex operations in new environments without additional training.
Editorial context：The article explains how GPT-6 Astra controls the Unitree G1 robot to perform kitchen tasks using a three-step process: spatial exploration, simulation mapping, and task execution. It highlights the integration of perception, planning, and control systems, and discusses the role of pre-trained models and skill-based execution in enabling generalization across new environments.
Zhixuan Robotics has deployed 100 units of the Lingxi X2 humanoid robot in 100 retail stores of Aishida, achieving a 39% increase in store sales. The robots, named 'Aibao,' engage customers by understanding their cooking needs and guiding them toward suitable products, while also seamlessly transferring conversations to human staff when necessary. This marks a milestone in the deployment of embodied AI in real-world retail environments.
Editorial context：This report highlights a significant deployment of humanoid robots in retail environments, showcasing how they integrate with human staff to improve sales performance. The case study with 100 robots in 100 stores demonstrates the practical application of embodied AI in real-world commerce, emphasizing the importance of collaboration between robots and human workers.
Sergey Levine@svlevineEditorial score6565Over the weekend, I put an unreleased checkpoint of π0.7 inside an excavator and placed 2nd at the @ActorLabs + @physical_int 36hr hackathon. With about an hour of embodied data (3 cameras and joystick values, no joint angles), the policy could continuously move dirt with a single prompt. This was so straightforward to get working (pi is cooking) we spent the rest of the hackathon mounting a Nerf minigun on the roof. We added a people searching/tracking + firing feature to prevent people from getting too close to the dangerous machinery (ai safety feature). Here’s how we built it + more details (data collection, hardware hax, sim2real, video of me getting shot)🧵
Researchers from EPFL and NYU have developed ScaFi, a scalable robotic fish that mimics the swimming motion of fish like cod and mackerel. The robot's design allows for proportional scaling of its tail structure while keeping the motor and tendon system consistent, enabling operation in various aquatic environments. Field tests showed that ScaFi maintains fish-like swimming behavior across different sizes, though energy efficiency and stability vary with scale.
This article explores the complexity of dexterous hands in real-world tasks, pointing out that evaluation criteria have shifted from single parameters to overall operational capabilities. Eight companies analyze, from standards, hardware, perception, data, models to commercialization, how to achieve the reliability and practicality of dexterous hands. The article emphasizes the integration of vision and tactile sensing, the importance of data loops, and the challenges between model training and real-world deployment.
Editorial context：This article provides a comprehensive overview of the challenges and approaches in evaluating and developing dexterous robotic hands, emphasizing the integration of hardware, perception, data, and models. It highlights the need for industry standards, the role of vision and tactile sensing, and the importance of data collection and model training for real-world deployment.
Vikash Kumar ✈️IROS2026@VikashplusEditorial score1515China is pursuing a strategic roadmap through its Five-Year Plans to dominate the global robotics industry, focusing on embodied AI and humanoid robotics. The 13th and 14th FYPs laid the foundation for industrial automation, while the 15th FYP emphasizes embodied intelligence, with state support for R&D and mass deployment of humanoids. Despite achievements in market share and production scale, challenges remain in precision hardware and semiconductor self-sufficiency, with risks of overcapacity and market volatility.
Editorial context：This analysis provides a detailed overview of China's strategic approach to robotics through its Five-Year Plans, highlighting the shift from industrial automation to embodied AI and the challenges in achieving self-sufficiency in critical components. It emphasizes the role of state coordination, domestic manufacturing capabilities, and the risks associated with the rapid expansion of humanoid机器人.
MIT researchers have developed a reconfigurable robotic lab that autonomously assembles, tunes, and dismantles optical experiments. The system uses robotic arms, 3D-printed component housings, and a cloud-based interface to enable remote operation. It can build and fine-tune a laser cavity in under 30 minutes, demonstrating the potential for fully automated optical experiments.
Editorial context：This research introduces a reconfigurable robotic optics lab capable of autonomously assembling, tuning, and dismantling optical experiments with micron-scale precision. The system integrates robotic arms, 3D-printed component housings, QR code identification, and a cloud-based interface for remote operation. It demonstrates the potential for fully automated optical experiments, reducing manual t犯
This article explores how tactile data is helping robots improve their dexterous manipulation skills. Researchers are creating large tactile datasets and models that can use tactile feedback to enhance robot performance in tasks like folding laundry or turning keys. Challenges include the difficulty of integrating tactile data with vision-based models and the need for more diverse and scalable datasets to achieve significant improvements in robot dexterity.
Editorial context：The article highlights the growing importance of tactile data in advancing robot dexterity, emphasizing the challenges of integrating tactile feedback into vision-language-action (VLA) models. It discusses recent research efforts to create diverse tactile datasets and models that can generalize across different robotic hardware, while also addressing the limitations of current approaches and the '
Unitree@UnitreeRoboticsSignalEditorial score6363
Editorial context：Unitree Robotics has open-sourced its UnifoLM-WLA-1.0 humanoid foundation model, which demonstrates strong cross-task and cross-end-effector generalization capabilities across desktop and whole-body manipulation tasks.
Aletta, the first autonomous blood-draw device approved for use in the U.S., uses imaging and robotics to perform blood draws with high success rates, even in challenging cases. While it addresses staffing shortages in clinical labs, concerns about skin tone bias and sample quality persist, requiring further validation.
Editorial context：Aletta, the first autonomous blood-draw device authorized in the U.S., combines imaging and robotics to perform blood draws with high success rates, though concerns about skin tone bias and sample quality remain. The device addresses staffing shortages in clinical labs but requires further validation to ensure equitable performance across all demographics.
Researchers at the University of Queensland have developed 'Paraborgs'—cyborg cockroaches equipped with needles and cameras to assist in search-and-rescue missions. These insects, grafted with electronic interfaces, can navigate rubble, deliver drugs, and operate in teams. The study addresses challenges in autonomy, communication, and human interaction with the technology.
Editorial context：This research explores the use of cyborg cockroaches for search-and-rescue operations, leveraging the natural mobility of insects and augmenting them with electronics for sensing and intervention. The study highlights challenges in autonomy, communication, and human acceptance, while emphasizing the potential for rapid deployment in disaster scenarios.
Researchers from MIT Lincoln Laboratory deployed sensors in the Arctic to monitor under-ice sounds and test through-ice communication using a magnetic modem. The study addresses challenges in extreme weather and highlights the importance of community collaboration and sensor deployment strategies for Arctic research.
Editorial context：This research focuses on through-ice communication and acoustic monitoring in the Arctic, using low-cost sensors and magnetic modem technology. The study highlights the challenges of deploying and retrieving equipment in extreme conditions and emphasizes the importance of community engagement and collaboration with local experts.
Skild AI introduces S1, a robotic foundation model that leverages in-context learning to execute complex, long-horizon tasks without post-training. This marks a significant shift from traditional fine-tuning approaches, enabling rapid deployment and reducing data requirements. The model demonstrates strong performance on unseen tasks, including plant potting, pancake cooking, and kit assembly, and shows robustness to perturbations and common-sense reasoning.
Editorial context：Skild AI introduces S1, a robotic foundation model that leverages in-context learning to execute complex, long-horizon tasks without post-training. This marks a significant shift from traditional fine-tuning approaches, enabling rapid deployment and reducing data requirements. The model demonstrates strong performance on unseen tasks, including plant potting, pancake cooking, and kit assembly, and
Google DeepMind has released Gemini Robotics 2, a new model that enables robots to perform complex tasks with whole-body intelligence, advanced dexterity, and multi-robot collaboration. The model supports real-time reasoning, on-device adaptation, and safety features for human-robot interaction.
Editorial context：Google DeepMind introduces Gemini Robotics 2, a significant advancement in whole-body control and multi-robot collaboration for embodied AI. The release highlights improvements in dexterity, reasoning, and on-device adaptation, with a focus on safety and real-world task execution.
Firefly Aerospace's Blue Ghost Mission 2 will deploy NVIDIA Jetson for on-orbit AI processing, enabling real-time lunar data analysis and reducing latency. This marks the first use of Jetson in lunar orbit, supporting scientific research and future lunar exploration.
Editorial context：NVIDIA Jetson's deployment in lunar orbit marks a significant step in edge AI for space applications, enabling real-time data processing and reducing reliance on Earth-based computation.
Google DeepMind has released Gemini Robotics-ER 1.6, an upgraded model that enhances embodied reasoning for robotics. This model improves spatial reasoning, multi-view understanding, and safety compliance, enabling robots to perform complex tasks like instrument reading. It is available via the Gemini API and Google AI Studio, with examples provided in a developer Colab.
Editorial context：Google DeepMind's Gemini Robotics-ER 1.6 represents a significant advancement in embodied reasoning for robotics, enhancing spatial reasoning, multi-view understanding, and safety compliance. It introduces instrument reading capabilities, crucial for industrial applications, and demonstrates improved performance over previous versions in both task success detection and safety instruction following
Dexterity's research introduces 'Transactable World Models' as a core component for Physical AI, treating world models as operators that reason about physical reality rather than storing data. These models enable robust manipulation by integrating physics, handling uncertainty, and supporting multi-agent coordination with explicit rollback and transaction guarantees. The approach emphasizes interpretability, real-time consistency, and the ability to reason about cause-and-effect relationships in dynamic environments.
Editorial context：Dexterity introduces 'Transactable World Models' as a foundational component for Physical AI, emphasizing interpretability, physics integration, and real-time consistency. This approach enables robust manipulation in complex environments by treating world models as operators rather than data stores, allowing for explicit uncertainty quantification and transaction guarantees essential for multi-ag,