Robot control
Sensor fusion
Definition
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.
Also known as: Multisensor fusion, Multi-sensor fusion
Updated
Complementary measurements support one estimate
A camera can observe scene structure while an IMU measures rapid rotational and inertial motion. Combining them can support visual-inertial odometry. Sensor fusion is the broader process; it is not the name of one particular algorithm.
The robot_localization package illustrates fusion of pose, velocity, odometry, and IMU messages with configurable choices about which variables to include.
More inputs are not automatically more information
Two reported values may come from the same underlying measurement. For example, wheel-derived position and velocity can share encoder errors. The configuration guide warns against feeding duplicate information into a filter as though it were independent evidence.
Frames and uncertainty must agree
The estimator documentation describes frame transformations, sensor timeouts, and covariance settings. These are part of the measurement interpretation. Combining a camera-frame velocity with a body-frame velocity without the correct transformation does not produce a meaningful robot estimate. Likewise, understated measurement uncertainty can make one unreliable source dominate the output.
Sources
Related terms
State estimation
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.
Inertial measurement unit
An inertial measurement unit is a sensor assembly that typically combines accelerometers and gyroscopes to measure specific force and angular velocity. Some devices also provide magnetometer readings or estimated orientation.
Visual-inertial odometry
Visual-inertial odometry estimates a moving system's motion by combining camera observations with inertial measurements. It typically estimates position, orientation, velocity, and sensor biases over time.