Unit 07 · lesson

Autonomous Is a Sequence of Verified Behaviors

Autonomous code has no driver available to rescue a bad assumption in real time.

That makes autonomous less about writing a long routine and more about composing behaviors you already trust.

Break the routine into claims

Weak plan:

Drive out, grab a piece, score it.

Better:

establish starting pose;
drive to acquisition zone;
run intake while approaching;
confirm possession or time out;
move to scoring pose;
prepare mechanism;
score;
enter a safe final state.

Each step has an entry condition, action, exit condition, and failure possibility.

Time is a weak sensor

A routine like “drive motor for 1.4 seconds” may work on a fresh battery and fail later because time does not directly measure distance.

Sensor-based motion uses encoders, gyro, odometry, or other feedback to estimate robot state.

That does not make it perfect. Wheel slip, calibration error, impacts, and starting-position error still exist.

Pose

A robot pose combines position and orientation in a coordinate system.

Conceptually:

pose = (x position, y position, heading)

Path-planning and odometry systems use pose estimates to reason about where the robot is and where it should go.

Build an autonomous state table

State	Entry condition	Action	Exit condition	Failure response
start	auto enabled	establish pose	pose ready	stop / conservative routine
acquire	path begins	drive + intake	piece detected or timeout	continue safe fallback
score	scoring position	run scoring sequence	action complete	stop mechanism
finish	routine complete	hold/stop	auto ends	safe state

Your table does not need to control a real robot yet. It needs to make logic visible.

Test small before long

A good autonomous build sequence is:

verify one mechanism command
→ verify one sensor
→ verify one short movement
→ verify start/stop behavior
→ combine two behaviors
→ log result
→ expand

Do not begin by debugging a fifteen-step routine.

Current planning tools

Modern FRC teams may use path-planning tools such as Choreo or PathPlanner. Tool choice matters less than understanding pose, constraints, trajectory following, and failure recovery.

Do not build new instruction around deprecated tooling simply because an old tutorial ranks high in search results.

Failure mode: perfect path, wrong starting condition

A mathematically correct path can fail if the robot starts from the wrong pose, the coordinate system is misunderstood, or the mechanism state is not ready.

Autonomous reliability begins before the first movement.

Add your state table and one bounded autonomous test plan to the Unit 7 evidence.