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This paper presents MOLA-LIO, a novel LiDAR-inertial odometry system designed for the COMFORT Localization Benchmark at IROS 2026. By integrating IMU data and optional legged kinematics, the architecture aims to improve localization accuracy in dynamic environments while maintaining real-time performance. The work represents a significant step forward in sensor fusion techniques critical for advanced autonomous navigation systems.
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MOLA LiDAR-Inertial Odometry (MOLA-LIO) on the COMFORT Localization Benchmark

arXiv1 min read

arXiv:2609.25813v1 Announce Type: new Abstract: This short report documents our entry to the COMFORT Localization Benchmark (IROS 2026), evaluated on the GrandTour dataset recorded with the Boxi payload. It extends MOLA-LO into a LiDAR-inertial system that also ingests IMU and, optionally, legged kinematic odometry. We describe the architecture, the streams consumed, the local protocol that selected the submitted configuration, and the measurements backing our real-time claim.

Abstract:This short report documents our entry to the COMFORT Localization Benchmark (IROS 2026), evaluated on the GrandTour dataset recorded with the Boxi payload. It extends MOLA-LO into a LiDAR-inertial system that also ingests IMU and, optionally, legged kinematic odometry. We describe the architecture, the streams consumed, the local protocol that selected the submitted configuration, and the measurements backing our real-time claim.

Robotics (cs.RO)

arXiv:2609.25813 [cs.RO]

(or arXiv:2609.25813v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.25813 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 154 words

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