The REMUS RLF Reader is a Python-based utility designed to parse and analyze REMUS-100 AUV Run Log Files (.RLF files) and accompanying ADCP data files (.ADC, .GPS, .rmf). Developed with a focus on data derived from the analyses of the Makua Beach dataset, this project facilitates easy access and manipulation of underwater AUV data collected off the coast of Hawaiʻi.

Key Features:

• Comprehensive Parsing: The reader decodes all known record types from the binary RLF format into user-friendly NumPy arrays. This includes high-rate sensor data, mission configurations, vehicle diagnostics, and event logs, ensuring a complete understanding of the data.
• Web Assembly Viewer: Utilize the Web Viewer, a powerful browser-based interactive explorer, allows for easy dragging and dropping of RLF files. Users can generate synchronized plots and access a virtual-scrolled message browser without sending any data outside their local browser environment.

Files Provided:

• remus_rlf.py - The main parser for RLF binary files.
• remus_adcp.py – The parser for ADCP companion files.
• REMUS_RLF_FORMAT_SPEC.txt - Details of the underlying binary format specifications based on empirical research.

Supported Record Types:

The parser recognizes and decodes various record types, including:

• High-Rate Sensor Data: Contains critical navigation, temperature, and salinity metrics.
• Mission and Configuration Data: Includes vehicle name, types, and mission state mapping.
• Diagnostics: Provides insights into vehicle health, including battery status and system errors.

Installation Requirements:

• Python 3.8+ and NumPy are essential, while Matplotlib is optional for generating plots.

Usage Examples:

Parsing an RLF file:

from remus_rlf import parse_rlf, print_summary

parsed = parse_rlf('130906/RLF/130906.RLF')
print_summary(parsed)

nav = parsed['Navigation']
print(nav['lat'], nav['lon'], nav['depth'])

Generating CLI Summary and Plots:

python remus_rlf.py 130906/RLF/130906.RLF
python remus_rlf.py 130906/RLF/130906.RLF --plot

Disclaimer:

This tool’s binary format specification relied heavily on pattern analysis; no official Hydroid/Kongsberg documentation was utilized. Users should validate output values against independent measurements to ensure data integrity.

For further details on the data used for parsing, refer to UC San Diego Library Digital Collections for the corresponding RLF and ADC datasets.