Validation of LIDAR-Based Odometry Using a Motion Capture System on a Scaled Autonomous Platform

Ensuring safe and reliable autonomous driving depends on robust positioning methods, which can be challenging to implement at full scale. Scaled indoor experimentation offers high measurement accuracy and system scalability, despite lacking full environmental realism. In this work, we present a comparative study of localization techniques using a custom-built scaled platform in an enclosed environment. We evaluate a LIDAR-based odometry strategy against a motion capture (MoCap) system by characterizing MoCap accuracy, comparing trajectories, estimating positioning errors, and analyzing limitations under visual interference. Our results support the use of MoCap as a reliable reference system for validating onboard odometry and lay the foundation for scalable, controlled testing environments for autonomous navigation systems.