Chris Paxton@chris_j_paxtonEditorial score1515#Embodied perception
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- Chris Paxton@chris_j_paxtonEditorial score1515
arXiv Robotics — research abstractsEditorial score7575 Towards a General Humanoid Loco-Manipulation Model via Egocentric Whole-Body Human Data Pretraining
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.
arXiv Robotics — research abstractsEditorial score6363 Whole-Body Aerial Grasping and Lifting via Partial Visual Observations
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.
arXiv Robotics — research abstractsEditorial score6161 IndoorBEV: A Lightweight Real-Time LiDAR BEV Perception System for Indoor Mobile Robots
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
RoboSpeak — WeChatSignalEditorial score8686 Motors Don't Need Upgrades, Robots Can Run Faster! Beihang University Science Subjournal Reveals New Logic for Quadruped Locomotion
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.
QbitAI — RoboticsSignalEditorial score8585 GPT-6 Astra Connects to Unitree G1, Cleans the Kitchen!
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.
Sergey Levine@svlevineEditorial score6565Quoted postsimon@nautsimon_Over 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)🧵
Science Robotics — Journal metadataEditorial score6363 ALBATROSS: A bioinspired, aerially deployable, autonomous sailing sensor platform
ALBATROSS is a hybrid bioinspired robot that passively autorotates for soft water landing and transitions into a wind-driven sailboat. It uses dual-function rigid wingsails and a biomimetic rudder for propulsion and maneuvering. The design integrates minimal actuation and passive dynamics, validated through wind tunnel testing and field experiments.
RobohubEditorial score6262 Small, medium or large, a robotic fish maintains its swimming ability
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.
High-tech Robotics — WeChatSignalEditorial score8585 The 'War' of Dexterous Hands: 8 Embodied Companies Show Off Their Skills
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 score1515
Alex Kendall@alexgkendallEditorial score1515
RobohubSignalEditorial score8585 Robotics Roadmaps from Around the World: Spotlight of the Month - China
China 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 — RoboticsSignalEditorial score8888 Robotic lab sets up and runs optics experiments on demand
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
IEEE Spectrum — RoboticsSignalEditorial score8585 Robots Are Learning to Feel
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 '
IEEE Spectrum — RoboticsSignalEditorial score8888 Cyborg Roaches Can Stab You With Needles
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.
MIT — RoboticsSignalEditorial score6565 Researchers tune into Arctic under-ice sounds and test through-ice communication
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 — BlogSignalEditorial score8585 Introducing S1: In-Context Learning for Robotics
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
Dexterity — BlogSignalEditorial score8888 Transactable World Models
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,