Radar Perception for All-Weather Autonomy

We witness wider adoption of autonomous robots in our society. This means they will need to work reliably for long-term autonomy, even facing adverse weather conditions, such as dense fog, heavy rain and snowfall. Although last decades the robotics community has made significant progress in these areas, achieving robust and reliable perception in all-weather conditions is still challenging.

The robustness and performance of robot autonomy strongly rely on its perceptual capability, for which radar technology is considered as indispensable. Compared with the popular vision and LiDAR techniques, radar sensing clearly offers some merits: longer range, measurement of relative velocity from Doppler effect, and robust operation in extreme weather conditions. However, its noisy characteristic caused by multi-path reflection, speckle noise and so on also bring in new problems on radar based robot perception, e.g., localization, mapping, SLAM and navigation, which requires significant fundamental research to tackle.

This Workshop aims to provide a platform for researchers, from both academia and industry, to share the state-of-the-art advances and lessons learned on radar perception, exchange ideas, and identify key challenges and opportunities to advance this field.