7 papers · 1 filter
Sensor Configuration Matters: A Systematic Evaluation of Multimodal SLAM on Quadruped Robots
Roberto Corlito, Fabian Schmidt, Nils Seibert +3
Autonomous navigation of quadrupedal robots in diverse environments fundamentally relies on resilient Simultaneous Localization and Mapping (SLAM). While visual-inertial SLAM has m…
Integration of Visual SLAM into Consumer-Grade Automotive Localization
Luis Diener, Jens Kalkkuhl, Markus Enzweiler
Accurate ego-motion estimation in consumer-grade vehicles currently relies on proprioceptive sensors, i.e. wheel odometry and IMUs, whose performance is limited by systematic error…
Radar-Based Odometry for Low-Speed Driving
Luis Diener, Jens Kalkkuhl, Markus Enzweiler
We address automotive odometry for low-speed driving and parking, where centimeter-level accuracy is required due to tight spaces and nearby obstacles. Traditional methods using in…
Lateral Velocity Model for Vehicle Parking Applications
Luis Diener, Jens Kalkkuhl, Markus Enzweiler
Automated parking requires accurate localization for quick and precise maneuvering in tight spaces. While the longitudinal velocity can be measured using wheel encoders, the estima…
ROVER: A Multi-Season Dataset for Visual SLAM
Fabian Schmidt, Julian Daubermann, Marcel Mitschke +4
Robust SLAM is a crucial enabler for autonomous navigation in natural, semi-structured environments such as parks and gardens. However, these environments present unique challenges…
Visual-Inertial SLAM for Unstructured Outdoor Environments: Benchmarking the Benefits and Computational Costs of Loop Closing
Fabian Schmidt, Constantin Blessing, Markus Enzweiler +1
Simultaneous Localization and Mapping (SLAM) is essential for mobile robotics, enabling autonomous navigation in dynamic, unstructured outdoor environments without relying on exter…