Introduction
Learn to create reliable autonomous routines using path planning, localization, and sensor-driven decision-making
What is Autonomous Programming?
Autonomous programming is the art of making your robot operate independently without driver input. During the 30-second autonomous period in FTC matches, your robot must navigate the field, detect game elements, and score points — all on its own.
Unlike driver-controlled periods where you're constantly adjusting, autonomous requires your robot to:
- Plan paths from start to finish
- Localize itself to know where it is on the field
- Make decisions based on sensor data
- Execute tasks precisely and repeatably
Why Autonomous Matters
In FTC DECODE (2025-2026), autonomous is worth significant points:
- Delivering ARTIFACTS to the OBELISK
- Detecting MOTIF patterns with AprilTags
- Parking in designated zones
- Setting up for driver-controlled period
Teams with strong autonomous routines consistently outperform those without, often winning matches before the driver-controlled period even begins.
Core Concepts in Autonomous
Motion Planning
How your robot decides where to go and what path to take. This includes:
- Straight-line movements vs curved paths
- Staying within boundaries
- Timing movements with mechanism actions
Localization & Odometry
How your robot knows where it is on the field:
- Dead reckoning (encoders, IMU)
- Sensor fusion (combining multiple data sources)
- Visual localization (AprilTags, computer vision)
Control & Execution
How your robot follows the plan accurately:
- PID controllers for precise movement
- Motion profiling for smooth acceleration
- Pure pursuit for curved path following
Building Your First Autonomous
Here's what you'll learn in this section:
- Time vs Encoder-Based Movement — Start simple before going advanced
- Odometry Basics — Track your robot's position on the field
- Motion Planning — Choose the right path planning method
- Pure Pursuit — Follow smooth, curved paths with precision
- Sensor Fusion — Combine multiple sensors for better accuracy
Autonomous Strategy Tips
Start Simple, Then Optimize: Your first autonomous doesn't need to be complex. A reliable 2-3 task routine beats an unreliable 5-task routine every time!
Development Process
- Plan on paper first — Draw your robot's path on a field diagram
- Start with time-based — Get basic movement working
- Add encoders — Make movements more consistent
- Implement odometry — Start tracking position
- Use vision — Detect game elements and align precisely
- Test, test, test — Practice matches reveal issues early
Competition Priorities
Early Season (Weeks 1-4):
- Time-based movement to scoring zones
- Basic game element detection with color sensors
- Simple parking routine
Mid Season (Weeks 5-8):
- Encoder-based precise movements
- Dead reckoning odometry (2-wheel or 3-wheel)
- AprilTag localization for alignment
Late Season (League Championships):
- Full path following (Pure Pursuit, Road Runner)
- Sensor fusion for robust localization
- Multiple autonomous routes based on alliance color and randomization
Common Mistakes to Avoid
Complex autonomous on day one — Start simple, add complexity gradually
No testing on actual field — Carpet type, battery voltage, and lighting all affect performance
Hardcoded delays — Time-based waits are unreliable; use sensor feedback when possible
Single autonomous route — Always have a backup plan if vision fails
Ignoring initialization time — Robot takes time to initialize; account for this in planning
Next Steps
Ready to build your autonomous routine? Start with Time vs Encoder-Based Movement to understand the fundamentals, then progress to Odometry for position tracking!