June 2026: Delivered data integrity improvements and labeling stability across perception pipeline, with a focus on business value and reliable analytics. Implemented token reuse to prevent duplicate EgoPose and VehicleState entries, upgraded the perception dataset dependency to surface fixes, and stabilized 3D auto-labeling label categories for consistent categorization. Added comprehensive tests and release-level adjustments to improve maintainability and reliability.

May 2026 monthly summary for tier4_perception_dataset focusing on data handling improvements and release readiness. The work this month centers on optimizing JSON serialization, reducing payload size, and preparing a stable release for downstream consumers.

April 2026: Key INS-based geolocation and perception dataset enhancements delivered for tier4_perception_dataset. Implemented optional geolocalization from INS, added num_pts_feats support, improved timestamp handling, and refactored LiDAR point count calculation for more robust data processing. Updated tests and documentation, added new test data, and aligned dependencies and CI tooling (httpx, pypcd4). Cleanups included removing unused velocity and oxts_msgs to improve stability. Commits: 5cbcdd6657cbd225265e8b2c11359cf634ebd950; e9dcc6fd5e34f8e6ad098863ae37defb854ec935; 08e96c5ae54bfb9d53d2e582adc77aeeb8d0cc4b.

March 2026: Tier4/AWML focused on reliability and automation improvements in the streaming and labeling pipelines. Key features delivered: Auto-labeling 3D improvements for WebAuto integration with improved timestamp handling and updated model configuration. Major bugs fixed: GroupStreamingSampler now processes the first element of sequences during sampling, eliminating a consistent data-skipping issue. Overall impact: enhanced data integrity, faster end-to-end auto-labeling workflows, and reduced configuration drift, enabling more accurate and timely analytics in production. Technologies/skills demonstrated: code fixes and configuration updates in streaming pipelines, 3D labeling workflows, and WebAuto integration patterns with a commit-driven approach.