Object Recognition and Navigation using a Single Networking Device.

Tomorrow's autonomous mobile devices need accurate, robust and real-time sensing of their operating environment. Today's solutions fall short. Vision or acoustic-based techniques are vulnerable against challenging lighting conditions or background noise, while more robust laser or RF solutions require either bulky expensive hardware or tight coordination between multiple devices. This paper describes the design, implementation and evaluation of Ulysses, a practical environmental imaging system using colocated 60GHz radios on a single mobile device. Unlike alternatives that require specialized hardware, Ulysses reuses low-cost commodity networking chipsets available today. Ulysses' new imaging approach leverages RF beamforming, operates on specular (direct) reflection, and integrates the device's movement trajectory with sensing. Ulysses also includes a navigation component that uses the same 60GHz radios to compute \"safety regions\" where devices can move freely without collision, and to compute optimal paths for imaging within safety regions. Using our implementation of a small robotic car prototype, our experimental results show that Ulysses images objects meters away with cm-level precision, and provides accurate estimates of objects' surface materials.