How can we enable high quality perception for robots navigating in harsh environments with smoke or fog? Camera or lidar based perception would suffer in these conditions. We explore a millimeter wave radar based perception for seeing past these occlusions. We combat the poor spatial resolution of these radars by training an end-to-end deep learning super-resolution network that outputs lidar-like point clouds from just a cheap, single-chip radar! We also show RadarHD’s robustness in smoke by testing with smoke bombs in a smoke chamber.
Top-5 Demos (MobiCom 2023)