Robot control
State estimation
Definition
State estimation infers quantities describing a robot or its environment from measurements and a model. A robot state may include position, orientation, velocity, and other variables that are not all directly measured.
Also known as: Robot state estimation
Updated
Measurements are evidence about a state
A camera, joint encoder, or inertial sensor measures only part of what a controller needs. An estimator combines available evidence with a model to infer a useful state. The robot_localization documentation gives a concrete implementation that tracks position, orientation, velocities, and linear accelerations.
For a walking robot, body orientation and velocity are examples of quantities that can inform balance control. The exact state vector depends on the application; it is not fixed by the phrase state estimation.
Prediction and correction
A model predicts how the state changes between observations. New observations correct the prediction. ROS's estimator documentation describes this pattern for an extended Kalman filter, including prediction-only operation when a sensor times out.
An estimate has uncertainty
Covariance represents uncertainty within these filters. A stream of smooth numbers does not mean the underlying state is known exactly. Missing measurements, uncertain models, and an unsuitable state representation affect the result. Pose estimation is a narrower example that focuses on position and orientation rather than every variable in a full robot state.
Sources
Related terms
Kalman filter
A Kalman filter is a recursive estimator that predicts a system's state with a linear model and corrects that prediction using noisy measurements. It tracks both the estimate and its error covariance.
Sensor fusion
Sensor fusion combines information from multiple sensors or estimation sources to produce a shared estimate. The combination must account for coordinate frames, timing, uncertainty, and dependence between inputs.
Pose estimation
Pose estimation determines the position and orientation of an object or robot relative to a reference frame. For a rigid body in three-dimensional space, a full pose has three translational and three rotational degrees of freedom.