Daredevil: Imaging Radar for Small Unmanned Ground Vehicles

For the Daredevil Project, iRobot Corporation proposes to integrate the output of inexpensive, low-power, UWB radar sensors with higher-resolution range imaging devices to provide sensing for small UGVs. For Phase I, the key objectives will be to develop sensor configurations and processing algorithms to enable the system to reliably detect obstacles through foliage and through rain and snow. A unique feature of our approach is the use of polarimetric radar to distinguish foliage from solid objects. Common types of foliage (tall grass, open fields, crop fields) provide strong radar returns for vertically-polarized radar pulses and weak radar returns for horizontally-polarized radar pulses. In contrast, objects such as rocks reflect radar roughly equally regardless of pulse orientation. By computing the differential reflectivity of the target object, we expect to reliably distinguish vertically-oriented vegetation from other solid objects. For the Phase I Option, we will fuse the sensor returns from the UWB radar sensors with the high-resolution range data from a SICK LIDAR. During Phase II, we will complete the system design and build two fully-integrated prototypes. Each prototype will include a PackBot robot platform, UWB radar sensors, LIDAR, and stereo vision.