LOCOMOTIONCURRENT2026-06-15

ADAPT: Analytical Disturbance-Aware Policy Training for Humanoid Locomotion

Bofan Lyu, Jindou Jia, Kuangji Zuo, Yanshuo Lu, Shijia Han, Gen Li, Boyu Ma, Jingliang Li, Geng Li, Jianfei Yang

This paper shows how to make humanoid robots handle unexpected pushes and forces while walking by analytically estimating disturbances from Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. Movement, Mechanics & Robot BodyDynamicsThe study of motion including forces, torques, mass, and inertia. rather than relying on force sensors or broad Simulation & Sim-to-RealRandomizationIntroducing controlled variability during simulation or training.. A developer can use ADAPT's disturbance observer to give Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running. policies explicit awareness of external forces, enabling robots to maintain stability and accuracy under real-world Movement, Mechanics & Robot BodyContactPhysical interaction between the robot and an object or surface. scenarios without task-specific tuning.

THE PROBLEM

This paper focuses on Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running.. This paper shows how to make humanoid robots handle unexpected pushes and forces while walking by analytically estimating disturbances from Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. Movement, Mechanics & Robot BodyDynamicsThe study of motion including forces, torques, mass, and inertia. rather than relying on force sensors or broad Simulation & Sim-to-RealRandomizationIntroducing controlled variability during simulation or training.. A developer can use ADAPT's disturbance observer to give Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running. policies explicit awareness of external forces, enabling robots to maintain stability and accuracy under real-world Movement, Mechanics & Robot BodyContactPhysical interaction between the robot and an object or surface. scenarios without task-specific tuning. Read the paper by tracking the Core ConceptsTaskThe job the robot is supposed to complete, such as pick-and-place, navigation, or drawer opening. definition, the Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. or data assumptions, and the evidence that supports the claimed improvement.

HOW IT WORKS

1

Task framing

The paper frames the work as Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running.. Start here because it defines what success means and which assumptions the rest of the method inherits.

2

Core method

This paper shows how to make humanoid robots handle unexpected pushes and forces while walking by analytically estimating disturbances from Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. Movement, Mechanics & Robot BodyDynamicsThe study of motion including forces, torques, mass, and inertia. rather than relying on force sensors or broad Simulation & Sim-to-RealRandomizationIntroducing controlled variability during simulation or training.. A developer can use ADAPT's disturbance observer to give Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running. policies explicit awareness of external forces, enabling robots to maintain stability and accuracy under real-world Movement, Mechanics & Robot BodyContactPhysical interaction between the robot and an object or surface. scenarios without task-specific tuning. When reading the method section, identify the inputs, the learned or engineered representation, and the Core ConceptsActionA command the robot sends to its motors, controller, or low-level system. or prediction produced by the system.

3

Data and supervision

For robotics work, the data story is part of the method: check whether the system depends on Imitation & Reinforcement LearningTeleoperation (teleop)A human remotely controlling the robot, often to collect demonstrations., Simulation & Sim-to-RealSimulationA virtual environment where robots can be trained or tested., internet video, human labels, or Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. rollouts.

4

Evaluation evidence

The paper should be judged through its Simulation & Sim-to-RealEvaluationMeasuring how well a robot system performs. protocol: what data is used, what Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. or simulator is tested, and which Evaluation & ResearchBaselineA reference method used for comparison. comparisons support the claim. Look for the gap between the headline result and the Simulation & Sim-to-RealDeploymentPutting the trained system on a real robot. setting you would actually care about.

KEY RESULTS

Main contributionConceptual contribution

This paper shows how to make humanoid robots handle unexpected pushes and forces while walking by analytically estimating disturbances from Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. Movement, Mechanics & Robot BodyDynamicsThe study of motion including forces, torques, mass, and inertia. rather than relying on force sensors or broad Simulation & Sim-to-RealRandomizationIntroducing controlled variability during simulation or training.. A developer can use ADAPT's disturbance observer to give Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running. policies explicit awareness of external forces, enabling robots to maintain stability and accuracy under real-world Movement, Mechanics & Robot BodyContactPhysical interaction between the robot and an object or surface. scenarios without task-specific tuning.

WHY DEVELOPERS SHOULD CARE

This paper shows how to make humanoid robots handle unexpected pushes and forces while walking by analytically estimating disturbances from Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. Movement, Mechanics & Robot BodyDynamicsThe study of motion including forces, torques, mass, and inertia. rather than relying on force sensors or broad Simulation & Sim-to-RealRandomizationIntroducing controlled variability during simulation or training.. A developer can use ADAPT's disturbance observer to give Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running. policies explicit awareness of external forces, enabling robots to maintain stability and accuracy under real-world Movement, Mechanics & Robot BodyContactPhysical interaction between the robot and an object or surface. scenarios without task-specific tuning.

LIMITATIONS

The main limitation to check is whether the claimed behavior holds outside the paper's reported setup. That means testing across different Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. embodiments, scenes, objects, and data distributions.

WHAT COMES NEXT

The practical next step is independent reproduction with clear baselines, ablations, and stress tests. For a developer, the useful follow-up is to map the paper's Navigation & LocomotionLocomotionMovement of the robot body through space, like walking, rolling, or running. assumptions onto a concrete Core ConceptsRobotA physical system with sensors and actuators that can observe the world and take actions. stack, then test the smallest version of the method that could run end to end.

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