feat: Add localization template with grid-based sensor fusion

Implements comprehensive robot localization system as third template option.
Teams can now start with professional positioning and navigation code.

Template Features:
- 12x12 field grid system (12-inch cells)
- Multi-sensor fusion (encoders, IMU, vision)
- Kalman-filter-style sensor combination
- Fault-tolerant positioning (graceful degradation)
- 21 files, ~1,500 lines, 3 passing tests

Core Components:
- GridCell/Pose2D/FieldGrid - Coordinate system
- RobotLocalizer - Sensor fusion engine
- OdometryTracker - Dead reckoning from encoders
- ImuLocalizer - Heading from gyroscope
- VisionLocalizer - Position from AprilTags

Sensor Fusion Strategy:
Priority 1: Vision (AprilTags) → ±2" accuracy, 100% confidence
Priority 2: IMU + Odometry → ±4" accuracy, 70% confidence
Priority 3: Odometry only → ±12" accuracy, 40% confidence

System gracefully degrades when sensors fail, maintaining operation
even with partial sensor availability.

Hardware Abstraction:
- Interfaces (Encoder, GyroSensor, VisionCamera)
- Mock implementations for unit testing
- Teams implement FTC wrappers for their hardware

Documentation:
- LOCALIZATION_GUIDE.md - System architecture and usage
- GRID_SYSTEM.md - Field coordinate reference
- README.md - Quick start and examples

Usage:
  weevil new my-robot --template localization
  cd my-robot
  ./gradlew test  # 3 tests pass in < 1 second

This teaches professional robotics concepts (sensor fusion, fault
tolerance, coordinate systems) not found in other FTC tools. Positions
Nexus Workshops as teaching advanced autonomous programming.

Updated src/templates/mod.rs to register localization template with
proper metadata and feature descriptions.

All tests passing (10/10 template tests).

templates/localization/docs/GRID_SYSTEM.md

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