FTC Robot Localization

For a robot to autonomously move around the field accurately, it needs to know where it is.

A human driver can look at the field and understand the robot's location. An autonomous program does not have that ability. Instead, the robot uses sensors to estimate its position.

This process is called localization.

What is Localization?

Localization is the process of determining where the robot is on the field.

A robot's position is represented using three values:

X position
Y position
Heading

Together, these values are called the robot's pose.

Pose = (X, Y, Heading)

For example:

X = 24 in
Y = 36 in
Heading = 90°

This tells the robot that it is 24 inches along the X-axis, 36 inches along the Y-axis, and facing 90 degrees.

Why Localization Matters

An autonomous program might tell the robot:

Drive to the scoring area
Turn toward the goal
Score

But the robot needs to know where it currently is before it can determine how to get there.

Without localization, the robot is essentially moving blind.

Even if the robot is commanded to drive exactly 24 inches, the result may not be exactly 24 inches because of:

Wheel slip
Uneven surfaces
Battery voltage changes
Mechanical inconsistencies
Collisions

These errors accumulate throughout an autonomous routine.

For example, if the robot consistently turns slightly too far, its estimated path can gradually diverge from its intended path.

Accurate localization allows the robot to continuously estimate its pose and use that information to make corrections.

How Does Localization Work?

A robot cannot directly measure its position on the field.

Instead, it measures movement using sensors and uses those measurements to estimate its new position.

For example, if a robot knows:

Previous pose:
(24, 36, 90°)

Movement:
+10 inches forward
+5 inches sideways
+5° rotation

it can calculate a new estimated pose.

New pose:
(19, 46, 95°)

The exact calculation depends on the localization system being used.

Different sensors provide different measurements of the robot's movement.

Common localization sensors include:

Drive motor encoders
Dead wheel encoders
IMUs
Cameras
AprilTags

These measurements can be combined to produce an estimate of the robot's pose.

Localization Error

Localization is an estimate, not a perfect measurement.

Every sensor introduces some amount of error.

For example, encoder-based localization can accumulate error because of:

Wheel slip
Incorrect wheel diameter measurements
Encoder inaccuracies
Mechanical flex
Incorrect calibration

This means the robot's estimated pose can gradually drift away from its actual position.

A good localization system minimizes this error and, when possible, uses multiple sensors to correct it.

Localization vs. Position

It is common to use "position" and "localization" interchangeably, but they are not exactly the same.

Position describes where the robot is.

Localization is the process used to estimate that position.

Think of it as:

Sensors
   ↓
Measurements
   ↓
Localization
   ↓
Estimated Pose

The estimated pose can then be used by other parts of the autonomous system.

Localization and Autonomous

Localization is one of the foundations of advanced autonomous systems.

A path-following system needs to know where the robot is so that it can determine whether the robot is following the desired path.

Sensors
   ↓
Localization
   ↓
Current Pose
   ↓
Path Following
   ↓
Motor Commands

For example, path-following libraries such as Road Runner and Pedro Pathing use a localization system to determine the robot's current pose while it moves.

Accurate localization therefore directly affects how accurately the robot can follow paths.

What's Next?

There are several ways an FTC robot can determine its pose.

The most common approaches use drive encoders, dead wheels, and IMUs, while more advanced systems can incorporate vision and other sensors.

Continue to Ways to Localize to learn how these systems work and how they compare.

Localization