RT Journal Article
T1 Loosely coupled 4D-Radar-Inertial Odometry for Ground Robots
A1 Coto Elena, Lucía
A1 Caballero, Fernando
A1 Merino, Luis
K1 Ground robots
K1 4D Radar-Inertial Odometry
K1 Doppler Velocity
AB Accurate robot odometry is essential for autonomous navigation. While numerous techniques have been developed based on various sensor suites, odometry estimation using only radar and IMU remains an underexplored area. Radar proves particularly valuable in environments where traditional sensors, like cameras or LiDAR, may struggle, especially in low-light conditions or when faced with environmental challenges like fog, rain or smoke. However, despite its robustness, radar data is noisier and more prone to outliers, requiring specialized processing approaches. In this paper, we propose a graph-based optimization approach (https://github.com/robotics-upo/4D-Radar-Odom.git) using a sliding window for radar-based odometry, designed to maintain robust relationships between poses by forming a network of connections, while keeping computational costs fixed (specially beneficial in long trajectories). Additionally, we introduce an enhancement in the ego-velocity estimation specifically for ground vehicles, both holonomic and non-holonomic, which subsequently improves the direct odometry input required by the optimizer. Finally, we present a comparative study of our approach against existing algorithms, showing how our pure odometry approach improves the state of art in all trajectories of the NTU4DRadLM dataset, achieving promising results when evaluating key performance metrics.
PB Springer Nature
YR 2025
FD 2025-09-23
LK https://hdl.handle.net/10433/24780
UL https://hdl.handle.net/10433/24780
LA en
NO J Intell Robot Syst 111, 107 (2025)
NO Proyectos de investigaciónPID2021-127648OB-C31TED2021- 132476B-I00
NO Departamento de Deporte e Informática
DS RIO
RD Apr 24, 2026