April 2025: Focus on boosting dev/test realism for Carla simulations in WATonomous/wato_monorepo. Delivered the reactivation of core simulation services by uncommenting relevant docker-compose entries for carla_ros_bridge and carla_sample_node, enabling their use in development and testing environments. This was implemented via commit 791cd777f9a3a1ddaa1472f8fd6aca3acbaa86e6 ('Uncomment simulation services').

February 2025 Monthly Summary for WATonomous/wato_monorepo: Delivered a new ROS 2 node BGRA to BGR Image Encoding Converter for multi-camera streams (center, right, left). The node subscribes to three camera feeds, converts image encoding from BGRA to BGR, and publishes BGR-encoded images. Output topics are dynamically configured based on the role_name parameter to ensure downstream systems receive data in the expected BGR format, enabling seamless integration across camera streams. This work aligns CARLA-sourced imagery with downstream perception components, reducing integration effort and accelerating pipeline readiness. Major bugs fixed: Fixed the BGRA to BGR conversion path to ensure correct color encoding and reliable downstream consumption, improving data integrity in multi-camera feeds. Overall impact and accomplishments: Establishes a standardized BGR feed across center/right/left camera pipelines, enabling faster integration with perception stacks, better data consistency, and improved system reliability. Demonstrates end-to-end capability from raw camera feeds to downstream consumers with dynamic topic routing. Technologies/skills demonstrated: ROS 2, image encoding conversion, multi-camera data handling, dynamic parameter-based topic configuration (role_name), CARLA integration, version-control traceability (commit 640fe6bdce227d280de9e2732a3aacbeffe096f0).

January 2025 monthly summary for WATonomous/wato_f1tenth: Delivered migration to the f1tenth_gym_ros simulation environment, removing Gazebo-specific artifacts and standardizing configuration references. Introduced new Docker-based tooling (Dockerfiles, entrypoint scripts, and a dedicated docker-compose for simulation) to enable reproducible environments and faster iteration. These changes reduce maintenance, simplify onboarding, and align with the team’s goal of more scalable, containerized testing workflows.