{
  "niche": "robotics-manipulation-labs",
  "count": 39,
  "records": [
    {
      "name": "IRIS Lab",
      "institution": "Stanford University",
      "lead": "Chelsea Finn",
      "focus": "robot learning, imitation & RL, manipulation foundation models",
      "hardware": "Franka / ALOHA-style arms",
      "notable_dataset": "ALOHA / Mobile ALOHA",
      "type": "academic",
      "country": "USA",
      "url": "https://ai.stanford.edu/~cbfinn/",
      "confidence": "high",
      "_sources": [
        "https://ai.stanford.edu/~cbfinn/"
      ]
    },
    {
      "name": "RAIL (BAIR)",
      "institution": "UC Berkeley",
      "lead": "Sergey Levine",
      "focus": "deep RL, offline RL, VLA models for control",
      "hardware": "WidowX / Franka",
      "notable_dataset": "BridgeData; Open X-Embodiment",
      "type": "academic",
      "country": "USA",
      "url": "https://rail.eecs.berkeley.edu/",
      "confidence": "high",
      "_sources": [
        "https://rail.eecs.berkeley.edu/"
      ]
    },
    {
      "name": "R-PAD",
      "institution": "Carnegie Mellon University",
      "lead": "Deepak Pathak",
      "focus": "self-supervised learning, generalization, manipulation",
      "hardware": "quadrupeds / arms",
      "notable_dataset": "PyRobot",
      "type": "academic",
      "country": "USA",
      "url": "https://r-pad.github.io/",
      "confidence": "high",
      "_sources": [
        "https://r-pad.github.io/"
      ]
    },
    {
      "name": "Improbable AI Lab",
      "institution": "MIT CSAIL",
      "lead": "Pulkit Agrawal",
      "focus": "sim-to-real, dexterous manipulation, RL",
      "hardware": "dexterous hands / Franka",
      "notable_dataset": "RialTo",
      "type": "academic",
      "country": "USA",
      "url": "https://improbableai.com/",
      "confidence": "high",
      "_sources": [
        "https://improbableai.com/"
      ]
    },
    {
      "name": "Perceptual Science Group (GelSight)",
      "institution": "MIT",
      "lead": "Edward Adelson",
      "focus": "vision-based tactile sensing for manipulation",
      "hardware": "GelSight sensors",
      "notable_dataset": "GelSight",
      "type": "academic",
      "country": "USA",
      "url": "https://persci.mit.edu/people/adelson",
      "confidence": "high",
      "_sources": [
        "https://persci.mit.edu/people/adelson"
      ]
    },
    {
      "name": "RPL",
      "institution": "UT Austin",
      "lead": "Yuke Zhu",
      "focus": "generalist robots, imitation/RL, sim frameworks",
      "hardware": "Franka / MuJoCo",
      "notable_dataset": "robosuite",
      "type": "academic",
      "country": "USA",
      "url": "https://rpl.cs.utexas.edu/",
      "confidence": "high",
      "_sources": [
        "https://rpl.cs.utexas.edu/"
      ]
    },
    {
      "name": "REAL",
      "institution": "Stanford University",
      "lead": "Shuran Song",
      "focus": "manipulation via interaction, diffusion policies",
      "hardware": "UR / Franka / UMI",
      "notable_dataset": "Diffusion Policy; UMI",
      "type": "academic",
      "country": "USA",
      "url": "https://real.stanford.edu/",
      "confidence": "high",
      "_sources": [
        "https://real.stanford.edu/"
      ]
    },
    {
      "name": "GRAIL",
      "institution": "NYU",
      "lead": "Lerrel Pinto",
      "focus": "large-scale robot learning, affordable open robots",
      "hardware": "low-cost arms / Stretch",
      "notable_dataset": "Robot Utility Models",
      "type": "academic",
      "country": "USA",
      "url": "https://wp.nyu.edu/grail/",
      "confidence": "medium",
      "_sources": [
        "https://wp.nyu.edu/grail/"
      ]
    },
    {
      "name": "IRoM-Lab",
      "institution": "Princeton University",
      "lead": "Anirudha Majumdar",
      "focus": "safe generalization, formal guarantees, manipulation",
      "hardware": "manipulators / drones",
      "notable_dataset": null,
      "type": "academic",
      "country": "USA",
      "url": "https://irom-lab.princeton.edu/",
      "confidence": "high",
      "_sources": [
        "https://irom-lab.princeton.edu/"
      ]
    },
    {
      "name": "RSE-Lab",
      "institution": "University of Washington",
      "lead": "Dieter Fox",
      "focus": "state estimation, perception, manipulation",
      "hardware": "Franka",
      "notable_dataset": "Open X-Embodiment contributor",
      "type": "academic",
      "country": "USA",
      "url": "https://homes.cs.washington.edu/~fox/",
      "confidence": "high",
      "_sources": [
        "https://homes.cs.washington.edu/~fox/"
      ]
    },
    {
      "name": "SVL",
      "institution": "Stanford University",
      "lead": "Jiajun Wu",
      "focus": "vision + manipulation, embodied AI benchmarks",
      "hardware": "OmniGibson / Franka",
      "notable_dataset": "BEHAVIOR; iGibson",
      "type": "academic",
      "country": "USA",
      "url": "https://svl.stanford.edu/",
      "confidence": "high",
      "_sources": [
        "https://svl.stanford.edu/"
      ]
    },
    {
      "name": "RL2",
      "institution": "Georgia Tech",
      "lead": "Danfei Xu",
      "focus": "visuomotor skill learning, imitation, world models",
      "hardware": "arms / Project Aria",
      "notable_dataset": "EgoMimic",
      "type": "academic",
      "country": "USA",
      "url": "https://rl2.cc.gatech.edu/",
      "confidence": "high",
      "_sources": [
        "https://rl2.cc.gatech.edu/"
      ]
    },
    {
      "name": "AUTOLAB",
      "institution": "UC Berkeley",
      "lead": "Ken Goldberg",
      "focus": "grasping, cloud robotics, manipulation",
      "hardware": "arms",
      "notable_dataset": "Dex-Net",
      "type": "academic",
      "country": "USA",
      "url": "https://autolab.berkeley.edu/",
      "confidence": "medium",
      "_sources": [
        "https://autolab.berkeley.edu/"
      ]
    },
    {
      "name": "Tactile Robotics Group (BRL)",
      "institution": "University of Bristol",
      "lead": "Nathan Lepora",
      "focus": "vision-based tactile sensing, tactile sim-to-real",
      "hardware": "TacTip / DIGIT",
      "notable_dataset": "TacTip",
      "type": "academic",
      "country": "UK",
      "url": "https://www.bristol.ac.uk/engineering/research/tactile-robotics/",
      "confidence": "high",
      "_sources": [
        "https://www.bristol.ac.uk/engineering/research/tactile-robotics/"
      ]
    },
    {
      "name": "Robotic Systems Lab (RSL)",
      "institution": "ETH Zurich",
      "lead": "Marco Hutter",
      "focus": "legged locomotion + loco-manipulation",
      "hardware": "ANYmal quadruped",
      "notable_dataset": "ANYmal platform",
      "type": "academic",
      "country": "Switzerland",
      "url": "https://rsl.ethz.ch/",
      "confidence": "high",
      "_sources": [
        "https://rsl.ethz.ch/"
      ]
    },
    {
      "name": "Robot Learning Lab",
      "institution": "Imperial College London",
      "lead": "Edward Johns",
      "focus": "dexterous manipulation, sim-to-real, one-shot imitation",
      "hardware": "arms / dexterous hands",
      "notable_dataset": "DOME",
      "type": "academic",
      "country": "UK",
      "url": "https://www.robot-learning.uk/",
      "confidence": "high",
      "_sources": [
        "https://www.robot-learning.uk/"
      ]
    },
    {
      "name": "A2I (Oxford Robotics Institute)",
      "institution": "University of Oxford",
      "lead": "Ingmar Posner",
      "focus": "robot learning, learning from demonstration",
      "hardware": "arms / quadrupeds",
      "notable_dataset": null,
      "type": "academic",
      "country": "UK",
      "url": "https://ori.ox.ac.uk/labs/a2i/",
      "confidence": "medium",
      "_sources": [
        "https://ori.ox.ac.uk/labs/a2i/"
      ]
    },
    {
      "name": "MVIG",
      "institution": "Shanghai Jiao Tong University",
      "lead": "Cewu Lu",
      "focus": "general robotic grasping/manipulation, vision + haptics",
      "hardware": "arms / grippers",
      "notable_dataset": "GraspNet-1Billion; AnyGrasp; RH20T",
      "type": "academic",
      "country": "China",
      "url": "https://www.mvig.org/",
      "confidence": "high",
      "_sources": [
        "https://www.mvig.org/"
      ]
    },
    {
      "name": "TEA Lab",
      "institution": "Tsinghua University",
      "lead": "Huazhe Xu",
      "focus": "embodied AI, visual RL, manipulation",
      "hardware": "arms / dexterous hands",
      "notable_dataset": "TEA-Lab open assets",
      "type": "academic",
      "country": "China",
      "url": "https://github.com/TEA-Lab",
      "confidence": "medium",
      "_sources": [
        "https://github.com/TEA-Lab"
      ]
    },
    {
      "name": "Cognitive Robotics (Kober group)",
      "institution": "TU Delft",
      "lead": "Jens Kober",
      "focus": "interactive robot learning, imitation from few demos",
      "hardware": "dual-arm manipulators",
      "notable_dataset": null,
      "type": "academic",
      "country": "Netherlands",
      "url": "https://www.tudelft.nl/en/staff/j.kober/",
      "confidence": "medium",
      "_sources": [
        "https://www.tudelft.nl/en/staff/j.kober/"
      ]
    },
    {
      "name": "Physical Intelligence",
      "institution": "Physical Intelligence Inc.",
      "lead": "Karol Hausman; Sergey Levine",
      "focus": "cross-embodiment VLA foundation models",
      "hardware": "third-party robot arms",
      "notable_dataset": "pi0 (openpi)",
      "type": "industry",
      "country": "USA",
      "url": "https://www.pi.website/blog/pi0",
      "confidence": "high",
      "_sources": [
        "https://www.pi.website/blog/pi0"
      ]
    },
    {
      "name": "Skild AI",
      "institution": "Skild AI",
      "lead": "Deepak Pathak; Abhinav Gupta",
      "focus": "omni-bodied robot foundation model",
      "hardware": "embodiment-agnostic",
      "notable_dataset": "Skild Brain",
      "type": "industry",
      "country": "USA",
      "url": "https://www.skild.ai/",
      "confidence": "high",
      "_sources": [
        "https://www.skild.ai/"
      ]
    },
    {
      "name": "NVIDIA GEAR (Isaac GR00T)",
      "institution": "NVIDIA",
      "lead": "Jim Fan; Yuke Zhu",
      "focus": "open humanoid foundation model + sim",
      "hardware": "partner robots (Fourier GR-1, 1X)",
      "notable_dataset": "Isaac GR00T N1.x",
      "type": "industry",
      "country": "USA",
      "url": "https://research.nvidia.com/publication/2025-03_nvidia-isaac-gr00t-n1-open-foundation-model-humanoid-robots",
      "confidence": "high",
      "_sources": [
        "https://research.nvidia.com/publication/2025-03_nvidia-isaac-gr00t-n1-open-foundation-model-humanoid-robots"
      ]
    },
    {
      "name": "Dyna Robotics",
      "institution": "Dyna Robotics",
      "lead": "Lindon Gao; Jason Ma",
      "focus": "world-action model, scaling via human video",
      "hardware": "robot arms",
      "notable_dataset": "DYNA-2 (1M+ hrs human video)",
      "type": "industry",
      "country": "USA",
      "url": "https://www.dyna.co/dyna-2",
      "confidence": "high",
      "_sources": [
        "https://www.dyna.co/dyna-2"
      ]
    },
    {
      "name": "Generalist AI",
      "institution": "Generalist",
      "lead": "Pete Florence; Andy Zeng",
      "focus": "embodied foundation models, general-purpose robots",
      "hardware": "robot-training gloves; cross-embodiment",
      "notable_dataset": "GEN-1",
      "type": "industry",
      "country": "USA",
      "url": "https://www.therobotreport.com/generalist-raises-400m-to-scale-its-general-purpose-ai-models/",
      "confidence": "high",
      "_sources": [
        "https://www.therobotreport.com/generalist-raises-400m-to-scale-its-general-purpose-ai-models/"
      ]
    },
    {
      "name": "Toyota Research Institute",
      "institution": "TRI",
      "lead": "TRI robotics team",
      "focus": "Large Behavior Models, diffusion policy, dexterity",
      "hardware": "bimanual manipulators; haptic teleop",
      "notable_dataset": "Diffusion Policy; LBMs",
      "type": "industry",
      "country": "USA",
      "url": "https://www.tri.global/our-work/robotics",
      "confidence": "high",
      "_sources": [
        "https://www.tri.global/our-work/robotics"
      ]
    },
    {
      "name": "Google DeepMind Robotics",
      "institution": "Google DeepMind",
      "lead": "team (Levine/Hausman collaborators)",
      "focus": "vision-language-action models at scale",
      "hardware": "many robot arms",
      "notable_dataset": "RT-1/RT-2/RT-X; Open X-Embodiment",
      "type": "industry",
      "country": "USA/UK",
      "url": "https://robotics-transformer-x.github.io/",
      "confidence": "high",
      "_sources": [
        "https://robotics-transformer-x.github.io/"
      ]
    },
    {
      "name": "Figure AI",
      "institution": "Figure AI",
      "lead": "Brett Adcock",
      "focus": "humanoid VLA (Helix), consumer + industrial",
      "hardware": "Figure 02 humanoid",
      "notable_dataset": "Helix VLA (~500 hrs teleop)",
      "type": "humanoid-company",
      "country": "USA",
      "url": "https://www.figure.ai/news/helix",
      "confidence": "high",
      "_sources": [
        "https://www.figure.ai/news/helix"
      ]
    },
    {
      "name": "1X Technologies",
      "institution": "1X Technologies",
      "lead": "Bernt Bornich",
      "focus": "consumer humanoid + world model",
      "hardware": "NEO humanoid",
      "notable_dataset": "1X World Model (Expert-Mode teleop)",
      "type": "humanoid-company",
      "country": "Norway/USA",
      "url": "https://www.1x.tech/discover/world-model-self-learning",
      "confidence": "high",
      "_sources": [
        "https://www.1x.tech/discover/world-model-self-learning"
      ]
    },
    {
      "name": "Tesla Optimus",
      "institution": "Tesla",
      "lead": "Optimus team",
      "focus": "factory humanoid; vision-only data collection",
      "hardware": "Optimus Gen 2/3",
      "notable_dataset": null,
      "type": "humanoid-company",
      "country": "USA",
      "url": "https://interestingengineering.com/culture/tesla-paying-to-train-optimus-robot",
      "confidence": "medium",
      "_sources": [
        "https://interestingengineering.com/culture/tesla-paying-to-train-optimus-robot"
      ]
    },
    {
      "name": "Agility Robotics",
      "institution": "Agility Robotics",
      "lead": "Peggy Johnson; Jonathan Hurst",
      "focus": "bipedal logistics robot; teleop-then-autonomous",
      "hardware": "Digit",
      "notable_dataset": null,
      "type": "humanoid-company",
      "country": "USA",
      "url": "https://www.agilityrobotics.com/",
      "confidence": "medium",
      "_sources": [
        "https://www.agilityrobotics.com/"
      ]
    },
    {
      "name": "Apptronik",
      "institution": "Apptronik",
      "lead": "Jeff Cardenas",
      "focus": "industrial humanoid; Robot Park data factory",
      "hardware": "Apollo",
      "notable_dataset": "Robot Park (teleop + AR)",
      "type": "humanoid-company",
      "country": "USA",
      "url": "https://apptronik.com/",
      "confidence": "high",
      "_sources": [
        "https://apptronik.com/"
      ]
    },
    {
      "name": "Sanctuary AI",
      "institution": "Sanctuary AI",
      "lead": "Daniel Friedmann",
      "focus": "teleop-collected behavioral + tactile data",
      "hardware": "Phoenix humanoid",
      "notable_dataset": "Carbon control system",
      "type": "humanoid-company",
      "country": "Canada",
      "url": "https://www.sanctuary.ai/",
      "confidence": "high",
      "_sources": [
        "https://www.sanctuary.ai/"
      ]
    },
    {
      "name": "AgiBot (Zhiyuan)",
      "institution": "AgiBot",
      "lead": "Peng Zhihui",
      "focus": "mass-produced humanoids + largest open dataset",
      "hardware": "AgiBot A2 / humanoids",
      "notable_dataset": "AgiBot World (1M+ trajectories)",
      "type": "humanoid-company",
      "country": "China",
      "url": "https://siliconangle.com/2024/12/30/chinas-agibot-releases-large-scale-humanoid-robot-ai-dataset-everyday-activities/",
      "confidence": "high",
      "_sources": [
        "https://siliconangle.com/2024/12/30/chinas-agibot-releases-large-scale-humanoid-robot-ai-dataset-everyday-activities/"
      ]
    },
    {
      "name": "Unitree Robotics",
      "institution": "Unitree",
      "lead": "Wang Xingxing",
      "focus": "low-cost humanoids/quadrupeds; open teleop tooling",
      "hardware": "G1 humanoid",
      "notable_dataset": "UnifoLM-WBT; unitree_lerobot",
      "type": "humanoid-company",
      "country": "China",
      "url": "https://www.unitree.com/mobile/opensource/",
      "confidence": "high",
      "_sources": [
        "https://www.unitree.com/mobile/opensource/"
      ]
    },
    {
      "name": "Fourier Intelligence",
      "institution": "Fourier Intelligence",
      "lead": "Alex Gu",
      "focus": "humanoid + care robots; open-source N1",
      "hardware": "GR-1 / GR-2 / N1",
      "notable_dataset": "Fourier N1 (open)",
      "type": "humanoid-company",
      "country": "China",
      "url": "https://www.fftai.com/",
      "confidence": "medium",
      "_sources": [
        "https://www.fftai.com/"
      ]
    },
    {
      "name": "UBTech Robotics",
      "institution": "UBTech",
      "lead": "Zhou Jian",
      "focus": "industrial humanoids; embodied-AI data centers",
      "hardware": "Walker S2",
      "notable_dataset": null,
      "type": "humanoid-company",
      "country": "China",
      "url": "https://www.prnewswire.com/news-releases/ubtech-humanoid-robot-walker-s2-begins-mass-production-and-delivery-with-orders-exceeding-800-million-yuan-302616924.html",
      "confidence": "medium",
      "_sources": [
        "https://www.prnewswire.com/news-releases/ubtech-humanoid-robot-walker-s2-begins-mass-production-and-delivery-with-orders-exceeding-800-million-yuan-302616924.html"
      ]
    },
    {
      "name": "Scale AI (Physical AI)",
      "institution": "Scale AI",
      "lead": "team",
      "focus": "teleop capture, sensor annotation, eval (data vendor)",
      "hardware": "client robots",
      "notable_dataset": "Physical AI data engine (service)",
      "type": "industry",
      "country": "USA",
      "url": "https://scale.com/blog/physical-ai",
      "confidence": "high",
      "_sources": [
        "https://scale.com/blog/physical-ai"
      ]
    },
    {
      "name": "Encord",
      "institution": "Encord",
      "lead": "team",
      "focus": "data layer for Physical AI: multimodal/point-cloud (data vendor)",
      "hardware": null,
      "notable_dataset": "Physical AI data platform (service)",
      "type": "industry",
      "country": "UK/USA",
      "url": "https://encord.com/physical-ai/",
      "confidence": "high",
      "_sources": [
        "https://encord.com/physical-ai/"
      ]
    }
  ],
  "_generated": "data-refinery"
}