FRC Robotics — Team 1389

Team 1389 Logo

2023 — Team 1389 | "Corb"

In the FIRST Robotics Competition Charged Up season, Team 1389 built Corb — a robot designed to score cones and cubes at all three heights and balance on the charging station. The robot featured a 4-wheel swerve drivetrain, a double-jointed arm, and a dual-roller intake capable of handling both game pieces in autonomous and teleop.

Corb Robot Corb Robot FRC Robotics

Robot Design

  • Drivetrain: 4-wheel swerve drive powered by 4 NEO and 4 NEO 550 motors — 360° movement and rotation for maximum field agility.
  • Arm: Double-jointed arm with 270° of rotation driven by NEOs at the base via a chain-and-sprocket system. Scores at all three heights.
  • Intake: Double-roller compliant wheel intake capable of picking up both cubes and cones from the ground and substations. A motorized "finger" roller allows cone rotation for backwards high-node scoring.

Programming

  • Auto-Balancing: Gyroscope-based system that drives the robot forward or backward until level within 2.5° — works from any approach angle using odometry.
  • Auto-Positioning: Preset arm positions using encoder feedback so drivers can score at any height with a single button press.
  • Path Tracking: Field-aware autonomous paths optimized through testing, accounting for holonomic swerve movement to maximize auton scoring.

2022 — Team 1389 | "Stargazer"

In the FIRST Robotics Competition Rapid React season, Team 1389 built Stargazer — a robot centered around fast and accurate cargo shooting. The robot featured several mechanically sophisticated systems working together to intake, index, and shoot balls with minimal driver input.

Stargazer Hanging Stargazer Stargazer

Robot Design

  • Drivetrain: Swerve drive for full 360° movement and precise field positioning.
  • Intake: Over-the-bumper intake that folds out to collect cargo from the field floor and bring it inside the robot frame.
  • Indexer: Lazy Susan-style rotating indexing system that queued and staged balls for consistent feeding into the shooter.
  • Turret: Rotating turret allowing the shooter to aim independently of the drivetrain, enabling shooting on the move without needing to face the hub.

Programming

  • Swerve Drive: Field-oriented swerve with NavX gyroscope, odometry for position tracking, and angle optimization per wheel for shortest-path rotation.
  • Turret Tracking: Limelight vision integrated via NetworkTables with a PID controller to automatically align the turret to the hub in real time.
  • Ball Detection: ML-based vision system detects power cells and uses a PID loop to turn the robot toward them autonomously during intake sequences.
  • Shooter RPM Control: Closed-loop flywheel velocity control via PID, with target RPM configurable from SmartDashboard for shooting at varying distances.
  • Automated Climbing: Sequential command groups execute a synchronized multi-stage climbing sequence, removing manual timing from the driver.

2020 — Team 1389 | "Andromeda"

In the FIRST Robotics Competition Infinite Recharge season, Team 1389 built Andromeda — a power cell shooting robot designed for reliability and versatility. The robot featured a tank drive, over-the-bumper intake, conveyor system, and a flywheel shooter with vision-assisted targeting.

Andromeda Andromeda Andromeda CAD

Robot Design

  • Drivetrain: Six-wheel tank drive with chain-in-tube, powered by 4 NEO motors with 5" Colson wheels for traction and reliability.
  • Intake: Over-the-bumper compliant wheel intake driven by a 775 Pro motor at 15:1, designed for fast and consistent power cell pickup.
  • Conveyor: Vertical belt conveyor with a bottom hopper, using Vex toothed aluminum-reinforced belts to feed power cells up to the shooter.
  • Shooter: Vertical dual-flywheel shooter with manually adjustable angle. Inner wheels spin at half the speed of outer flywheels via a pulley system, driven by two NEOs. Limelight mounted beneath for vision targeting.
  • Climber: Pneumatic piston arm that swings 120° to reach the shield generator bar, with NEO-powered winches and a ratchet to hold position after climbing.

Programming

  • Power Cell Detection: Custom machine learning model running on a Raspberry Pi 3B+ with a Google Coral Edge TPU, identifying power cells and publishing horizontal position to NetworkTables for autonomous alignment.
  • Autonomous Routines: Four routines including a reliable 6-ball auto — shoots 3 preloaded balls, drives to collect 3 more, realigns with Limelight, and shoots again.
  • Vision Targeting: Limelight 2+ with PID control loop for automatic alignment to the power port in both auto and teleop. Distance from target used to calculate optimal shooter speed.
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