PATH // 01
Researchers
Track papers, benchmarks and model families behind embodied intelligence.
OPEN PATH →Embodied AI — and its close cousin embodied robotics — is artificial intelligence that controls a physical body. VLA models, robot learning and Physical AI let these systems perceive, understand language, plan safely and act in the real world.
LIVE RESEARCH HUB Browse continuously updated topics, practical roadmaps, comparisons and weekly research signals in the Embodied AI Hub. Explore topics
CHOOSE YOUR PATH
Research teams, builders and business leaders need different entry points. These shortcuts connect the same evidence base to different decisions.
Track papers, benchmarks and model families behind embodied intelligence.
OPEN PATH →Jump to deployable resources, demos and open-source project references.
OPEN PATH →Map capabilities to use cases, workflows and value metrics before a pilot.
OPEN PATH →WHAT IS EMBODIED AI
Embodied AI fuses artificial intelligence with physical agents. Instead of only generating text or images, it helps robots navigate spaces, grasp objects, deliver medicine, inspect defects and complete real tasks.
Need the literal definition? Read What Is Embodied AI? — a definition-first hub with history, comparisons and FAQ.
Cameras, depth sensors, lidar and tactile signals help Embodied AI understand 3D space, object state and environmental change.
Vision-language models interpret goals, constraints and risk before a robot commits to an action.
Long tasks are decomposed into executable substeps with checks for collision, ambiguity and recovery.
Control policies drive arms, mobile bases and humanoid robots through contact-rich physical work.
Generative AI creates content.
Embodied AI changes reality.
CORE TECHNOLOGY STACK
VLA models, robot foundation models, world models, sim-to-real transfer and motion control form the full capability stack behind modern Robotics AI.
VLA Models connect what the robot sees, what humans say and what the robot should do.
VLA ModelsGeneral pretrained policies support many robot bodies, environments and task families.
Robot Foundation ModelsInternal predictors simulate object interaction and action consequences before execution.
World ModelsRobots train in digital twins and transfer skills to hardware with lower cost and risk.
Sim-to-RealRobots improve from human demonstrations, reinforcement feedback and real operating data.
Robot LearningHigh-level decisions become safe joint motions, contact handling and obstacle avoidance.
Motion ControlBrowse the live topic and resource index →
FAQ
Short answers for search intent, procurement discussions and early technical planning.
Embodied AI is artificial intelligence that controls a physical body — a robot arm, humanoid or autonomous vehicle — instead of only generating text or images. It uses sensors, VLA models and closed-loop control to perceive, plan and act in the real world.
It is more accurate to treat it as automation for dull, dangerous or highly repetitive physical tasks. Human supervision, workflow design, maintenance and exception handling remain important.
Autonomous driving is a major embodied AI domain: the vehicle perceives the physical world, reasons about motion and executes actions under safety constraints.
A VLA model connects visual input and language goals to action tokens or policies. It must account for geometry, timing, embodiment and physical feedback.
No. Humanoids are one embodiment. Mobile bases, robot arms, drones, autonomous vehicles and service robots can all use embodied AI techniques.
LIVE RESEARCH HUB
Browse continuously updated topics, practical roadmaps, comparisons and weekly research signals in the Embodied AI Hub.
// THE FUTURE IS PHYSICAL
From the latest arXiv surveys to factory deployments, Embodied AI, Robotics AI and Physical AI are becoming the next decade's core robotics stack.