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#CMU Robotics Institute

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2026-10-03Sat
  1. Chris Paxton65

    Chris Paxton discusses recent advancements in robot sports, particularly the tennis-playing robot from the LATENT paper, showcasing improved whole-body control in humanoid robots. However, he notes the current limitations in onboard sensing and perception, which often rely on external trackers. The post underscores the importance of closing this gap for future robotics development.

    Quoted postChris Paxton@chris_j_paxton

    What do robot sports teach us? We have seen incredibly cool progress in robot soccer and tennis recently, but just as interesting is what we definitely do not see. Robots are increasingly capable of incredibly fluid, reactive whole body control - but their ability to perceive the world while doing so is incredibly limited. And so we see shortcuts being taken, external trackers used, to avoid the limitations of onboard sensing and sensorimotor control while in challenging environments. The future of robotics will require closing this gap. Some thoughts -> https://itcanthink.substack.com/p/what-do-robot-sports-teach-us?r=3uj5js&utm_campaign=post&utm_medium=web

2026-10-02Fri
  1. arXiv Robotics — research abstracts75

    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.

  2. arXiv Robotics — research abstracts63

    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.

2026-09-30Wed
  1. arXiv Robotics — research abstracts60

    Bilinear World Models: Learning Representations with Structured Dynamics for Efficient Control

    This research proposes a JEPA-style world model with bilinear parameterization of latent dynamics, enabling efficient planning and control. The structured approach allows for action recoverability and prevents representation collapse, demonstrating success in both long-horizon planning and real-time control tasks.

  2. arXiv Robotics — research abstracts62

    KPI: A Promptable Kernel for Physical Interaction on Humanoids

    This research introduces KPI, a promptable kernel for physical interaction on humanoids, which allows trajectory sources to send contracts specifying force ranges and interaction behaviors. The kernel adapts stiffness, damping, and reference values in real-time based on tracking error and wrench estimates, enabling instruction-driven tasks like winch operation and door opening without task-specific code.

2026-09-29Tue
  1. RoboSpeak — WeChat83

    Built Over 100 Data Training Sites, Why Are Robots Still 'Hungry'?

    The article explores the issue of data scarcity in the field of embodied intelligence, pointing out that although there are already a large number of data collection centers, high-quality and reusable data remains severely insufficient. The article analyzes structural contradictions such as high data collection costs, inconsistent quality, fragmented formats, and lack of cross-ontology reusability. It introduces Wu Wen Tech's solution of building a data foundation through a Real2Sim2Real closed-loop system, including large-scale data collection, automated annotation, and simulation training technologies, ultimately forming a data-driven flywheel to promote the development of embodied intelligence.

    Editorial context：The article highlights the critical data scarcity in embodied AI, emphasizing the gap between the scale of robot models and the availability of high-quality physical interaction data. It identifies structural issues such as high collection costs, quality inconsistencies, and lack of standardization as major barriers. The solution proposed by Wu Wen Tech involves a Real2Sim2Real closed-loop system,

2026-09-28Mon
  1. High-tech Robotics — WeChat85

    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.

2026-09-26Sat
  1. Vikash Kumar ✈️IROS202615

    **Summary:** Vikash Kumar discusses his long-term focus on understanding human physical intelligence and translating that into embodied agents, highlighting the importance of studying human movement and interaction for developing advanced robotics. He looks forward to engaging with the robotics community at IROS2026, reconnecting with collaborators, and sharing progress on physical agent learning and action capabilities.

2026-09-04Fri