Precision Comparaison of Trimble SX12 against MOCAP

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. Technical Contribution: ROS2-Based Validation Framework To support the REISAR objectives, this project provides a ROS2-based framework for evaluating and comparing the accuracy of the Trimble SX12 total station against a high-precision motion capture (Mocap) system. The main objective is to validate the SX12 as a reliable ground truth reference for robotics and localization research. The package includes tools for: Visualizing and transforming trajectory data Analyzing static and dynamic evaluation scenarios Summary Table of Test Results The table below summarizes the main performance metrics for the three dynamic tests as well as the static test. Test Type Test Name RMSE (mm) MAE (mm) Max Error (mm) Mean Speed (m/s) Mean Accel. (m/s²) Max Accel. (m/s²) Dynamic Test Spiral Movement(Test1) 17.25 15.16 90.22 0.20 0.708 0.708 Zigzag MovementTest2) 47.13 40.38 349.12 0.20 1.996 5.614 Slalom(Test3) 24.73 23.08 89.82 0.20 0.708 3.354 Static Test 4 Static Points 4.72 4.56 6.73 - - - For reproducibility and further analysis, three ROS bags are attached below, each corresponding to a specific dynamic test (spiral, zigzag, and slalom movements). These datasets illustrate the exact experimental conditions and results discussed in the study.