rosbag2-analysis

Analyze rosbag2 data offline to extract trajectories by loading your bag recording and running a Python script that reconstructs paths from /odom data, generating trajectory plots and timing reports using pandas and matplotlib.

Analyze rosbag2 data offline to perform timing jitter analysis on high-rate ROS 2 topics by calculating velocity profiling and timing metrics, outputting the results as CSV files and plots for detailed inspection.

Rosbag2 analysis supports both sqlite3 and mcap formats for bag inspection and format comparison, extracting data using rosbag2_py to perform trajectory reconstruction and performance analysis across these storage types.

To analyze ROS 2 bag files for performance metrics, use Python libraries rosbag2_py, pandas, and matplotlib for data extraction, topic filtering, trajectory reconstruction, and generating CSV or plot outputs.

Filter specific ROS 2 topics when inspecting a rosbag2 file by applying topic filtering during offline analysis to isolate relevant high-rate topics for trajectory extraction and velocity profiling.