Week 3 of GSoC 2025 has been a milestone week! Building on the solid foundation from the previous weeks, this period was marked by significant technical breakthroughs, successful world migrations, and expanding the scope of our Gazebo migration project. The focus shifted from individual model migration to complete simulation environment migration, representing a major step forward in project complexity and practical application.

This week brought the satisfaction of resolving complex technical challenges while simultaneously opening new avenues for exploration. The successful completion of the simple obstacle world migration and the initiation of the auto-parking scenario migration demonstrate the growing maturity of our migration approach and methodology.

Preliminaries

Following the successful F1 Ackermann car model migration in Week 2, Week 3 began with a comprehensive review of the migrated components and identification of areas requiring refinement. Our weekly mentor meeting highlighted the importance of not just completing migrations but ensuring they function optimally within the Gazebo Harmonic ecosystem.

The primary focus evolved from basic model migration to sophisticated plugin optimization and complete world environment migration. With the foundational Ackermann model working in Harmonic, we could now address performance optimization, steering behavior refinement, and scaling up to complete simulation scenarios.

Our systematic approach continued to emphasize thorough testing and validation, ensuring that each migrated component not only functions but performs better than its Classic counterpart. The week's objectives reflected this maturation from basic compatibility to advanced optimization.

Objectives

  • Refine and optimize F1 Ackermann car Ackermann steering plugin behavior
  • Complete migration of simple_obstacle_world with F1 dummy cars as obstacles
  • Begin migration of auto-parking simulation scenario
  • Resolve plugin compatibility issues in auto-parking world

Execution

Ackermann Plugin Optimization

The week began with a deep dive into the Ackermann steering plugin behavior from Week 2. While the basic functionality was working, the steering response was overly sensitive and unrealistic for practical applications.

Issues Identified:

  • Excessive steering sensitivity to small angular velocity inputs
  • Steering angles exceeding realistic automotive ranges
  • Lack of proper steering rate limiting

Plugin Configuration Refinement:

  • Implemented realistic steering angle limits (±17° instead of ±54°)
  • Enhanced damping and friction for smoother operation
  • Synchronized steering wheel visual feedback with actual steering

Results Achieved:

  • Realistic car-like steering behavior
  • Smooth and controllable steering response
  • Proper proportional relationship between input and steering angle
  • Stable high-speed operation without oscillations

Simple Obstacle World Migration

The second major accomplishment was the complete migration of the simple obstacle world scenario, integrating multiple F1 dummy cars as static obstacles to create a realistic driving environment.

Migration Components:

1. World Structure Conversion

  • Migrated physics engine configuration to Harmonic standards
  • Implemented modern scene and lighting systems
  • Added ground plane with proper collision properties

2. F1 Dummy Car Integration

  • Positioned 12 F1 dummy cars as static obstacles
  • Ensured proper collision geometry for realistic interactions
  • Optimized visual meshes for performance

Auto-Parking World Migration Initiation

The week's final major initiative was beginning the migration of the auto-parking simulation scenario, representing a significant step up in complexity from previous migrations.

Scenario Analysis:

  • Lincoln vehicle with advanced sensor suite (3 lasers)
  • Multiple parked car obstacles with precise positioning
  • Road infrastructure with markings and boundaries
  • Complex interaction requirements for parking maneuvers

Completed Elements:

  • Basic world structure and physics configuration
  • Road infrastructure with realistic materials
  • Parking space markings and boundaries
  • Static obstacle car positioning

Plugin Compatibility Challenges

The auto-parking migration revealed several complex plugin compatibility issues that require dedicated resolution.

Issues Encountered:

  • Multi-Laser Integration: The Lincoln model requires three separate laser sensors
  • Sensor Plugin Updates: Classic sensor plugins need complete rewriting for Harmonic
  • Navigation Stack Integration: ROS navigation interfaces require updated bridge configurations
  • Coordinate Frame Management: TF tree compatibility between ROS2 and Gazebo Harmonic

Preliminary Solutions Identified:

  • Migrate to gz_ros2_control for sensor management
  • Implement ros_gz_bridge for topic integration
  • Update sensor configurations for Harmonic compatibility
  • Establish proper coordinate frame relationships

Challenges and Solutions

Steering Sensitivity Resolution

The most significant challenge was achieving realistic steering behavior. The initial migration produced overly sensitive steering that made the vehicle difficult to control.

Solution Approach:

  • Systematic parameter tuning through iterative testing
  • Implementation of proper damping and friction values
  • Addition of steering gain control for fine-tuning
  • Validation against real-world automotive specifications

World Migration Complexity

Migrating complete worlds rather than individual models introduced new challenges:

  • Coordinating multiple model migrations simultaneously
  • Ensuring consistent physics parameters across all elements
  • Managing performance optimization for complex scenes
  • Maintaining visual consistency and quality

Management Strategy:

  • Systematic component-by-component migration approach
  • Comprehensive testing at each integration step
  • Performance monitoring throughout the process
  • Detailed documentation of migration patterns

Advanced Sensor Integration

The auto-parking scenario's multi-sensor requirements highlighted the complexity of sensor plugin migration:

  • Multiple laser sensors with different configurations
  • Sensor data fusion and coordination
  • Real-time performance requirements
  • ROS2 integration complexity

Next Steps and Week 4 Focus

Auto-Parking Completion

  • Resolve remaining plugin compatibility issues
  • Complete Lincoln vehicle sensor integration
  • Implement ROS2 navigation stack compatibility
  • Validate parking scenario functionality

Technical Insights and Learnings

Migration Pattern Insights

Week 3 revealed several important patterns in successful Gazebo migration:

  • Incremental Approach: Component-by-component migration reduces risk and improves debugging
  • Parameter Optimization: Default values often require significant tuning for realistic behavior
  • Testing Integration: Continuous testing throughout migration prevents late-stage surprises

Reflection and Forward Look

Week 3 represents a significant maturation in our migration approach and capabilities. The progression from individual model migration to complete world scenarios demonstrates growing expertise and confidence in handling complex migration challenges.

The successful optimization of the Ackermann steering plugin shows that migration is not just about compatibility but about achieving better performance and behavior than the original implementation. This sets a high standard for future migration work.

The initiation of the auto-parking migration, while presenting new challenges, opens exciting possibilities for demonstrating the full capabilities of Gazebo Harmonic. The advanced sensor integration and navigation requirements will push our migration skills to new levels.

Key Takeaways:

  • Systematic optimization can improve upon original implementations
  • Complex world migration requires careful coordination and testing
  • Performance gains are achievable with proper migration techniques
  • Documentation and testing frameworks are essential for scalable migration work

Looking ahead to Week 4, I'm excited to tackle the remaining auto-parking challenges and establish our migration work as a comprehensive solution for the robotics community. The foundation built over the first three weeks positions us well for accelerated progress and expanding impact.

The journey from basic model migration to optimized world scenarios showcases the potential of systematic, well-tested migration approaches. I look forward to continuing this momentum and delivering robust, high-quality migration solutions!