With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …

Autonomous navigation requires both a precise and robust mapping and localization
solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well …

In this paper we present The Oxford Radar RobotCar Dataset, a new dataset for researching
scene understanding using Millimetre-Wave FMCW scanning radar data. The target …

Vehicle detection with visual sensors like lidar and camera is one of the critical functions
enabling autonomous driving. While they generate fine-grained point clouds or high …

Interest in autonomous vehicles (AVs) is growing at a rapid pace due to increased
convenience, safety benefits and potential environmental gains. Although several leading …

This paper introduces a multimodal range dataset namely for radio detection and ranging
(radar) and light detection and ranging (LiDAR) specifically targeting the urban environment …

The development of a navigation system is one of the major challenges in building a fully
autonomous platform. Full autonomy requires a dependable navigation capability not only in …

Numerous Simultaneous Localization and Mapping (SLAM) algorithms have been
presented in last decade using different sensor modalities. However, robust SLAM in …

We present an extensive comparison between three topometric localization systems: radar-
only, lidar-only, and a cross-modal radar-to-lidar system across varying seasonal and …

We survey the current state of millimeter-wave (mmWave) radar applications in robotics with
a focus on unique capabilities, and discuss future opportunities based on the state of the art …