DOI: 10.5281/zenodo.17152839
title: REISAR Underground Dataset with Ground Truth – Test of July & September  2025

description: Project Context: REISAR & France 2030

This work is part of the REISAR project (Advanced Robotic System for Sewer Network Inspection and Water Preservation), funded under the ANR-23-DMRO-0014 reference and supported by the France 2030 investment plan.

The REISAR initiative addresses major challenges in clean water access and sustainable resource management, in alignment with the United Nations' Sustainable Development Goals for 2030. Sewer networks, essential for wastewater transport, are often aging, difficult to access, and hazardous for maintenance personnel.

Starting in 2026, French regulations will require precise mapping (accuracy < 40 cm) of underground structures in sensitive areas, expanding to all urban zones by 2030. This project contributes directly to meeting these standards by validating high-precision localization technologies.

REISAR proposes an innovative robotic solution: a ground-based intelligent robot capable of navigating and inspecting sewer tunnels with minimal visual features. The project explores:



Robust localization in low-texture environments

Semantic data transmission from robots

User-friendly interfaces for non-experts

Training and operational safety improvements


The consortium(Pilgrim Technology , TRAAK , Conscience Robotics), ensuring a multidisciplinary approach. The “Made in France” nature of the solution highlights national technological excellence and its adaptability to other demanding environments.



REISAR Underground Dataset with Ground Truth – July & September 2025

The REISAR Underground Dataset – July & September 2025 was collected as part of the REISAR project under the Défi Transfert Robotique initiative, a collaboration between CESI LINEACT, Pilgrim Technology, and other industrial and academic partners. This dataset supports research in localization, sensor fusion, and autonomous navigation in underground-like environments.

The July 2025 recordings focus on validating multi-sensor integration and system synchronization in controlled indoor and outdoor settings. These tests served as a preparatory benchmark to ensure reliable data acquisition from RGB-D cameras, LiDAR, IMU, and ground truth systems such as the Trimble SX12 and TRAAK Wheere.

The newly added September 2025 ROS bags introduce more advanced and realistic scenarios, recorded inside underground pipes made of different materials, including PRV (Polyester Renforcé de Fibres de Verre) and concrete. These tests simulate operational conditions such as confined spaces, curved tunnels, and material-specific challenges, offering a richer benchmark for evaluating navigation robustness, sensor fusion algorithms, and terrain adaptation strategies.
description: Technical Description of the tests:

July 2025:

Test1 (rosbag2_2025_07_08-17_27_40):





System initialization sequence




Verification of sensor connectivity (LiDAR, IMU, RGB-D)




ROS topic publication check, no real motion analysis



Test2 (rosbag2_2025_07_08-18_20_40):





Low-speed manual teleoperation in an indoor rocky environment




Attempted terrain transition (failed due to obstacle)




Useful for evaluating localization in semi-structured indoor settings



Test3 (rosbag2_2025_07_09-12_11_09):





Corridor-like tunnel environment with inclined rocky ground




Intermittent Wi-Fi caused LiDAR data gaps




IMU inactive → useful for testing resilience to partial sensor loss



Test4 (rosbag2_2025_07_09-12_21_32):





Same corridor setup as Test3




SX12 ground truth tracking lost mid-test




ROS topic instability detected




Good for testing fallback odometry and dead-reckoning



Test5 (rosbag2_2025_07_09-14_49_19):





Indoor corridor run with full sensor coverage (TRAAK active)




IMU data stable and consistent




ROS topics stable




Benchmark-ready dataset for full sensor fusion



Test6 (rosbag2_2025_07_09-15_25_20):





High-speed short trajectory indoors




IMU inactive




Evaluates robustness of visual–LiDAR odometry at higher velocity



Test7 (rosbag2_2025_07_09-15_27_39):





Outdoor navigation on grass surface




IMU active, network stable




Provides outdoor reference dataset for comparison with indoor tests



Septembre 2025:

Test1 (rosbag2_2025_09_10-09_13_04, rosbag2_2025_09_10-09_33_00)



The test involves driving the robot inside a ring-shaped pipe, both with and without obstacles.

The main objective is to evaluate the robot’s motricity.

The test assesses the robot’s ability to navigate through and overcome various types of obstacles placed within the pipe.


 

 
description: detailed description will be found here: https://gitlab.com/lineact-valo/reisar_dataset