Title: Developing a Purely Visual Based Obstacle Detection using Inverse Perspective Mapping,
Abstract: Our solution is implemented in and for the frame of Duckietown. The goal of
Duckietown is to provide a relatively simple platform to explore, tackle and
solve many problems linked to autonomous driving. "Duckietown" is simple in the
basics, but an infinitely expandable environment. From controlling single
driving Duckiebots until complete fleet management, every scenario is possible
and can be put into practice. So far, none of the existing modules was capable
of reliably detecting obstacles and reacting to them in real time. We faced the
general problem of detecting obstacles given images from a monocular RGB camera
mounted at the front of our Duckiebot and reacting to them properly without
crashing or erroneously stopping the Duckiebot. Both, the detection as well as
the reaction have to be implemented and have to run on a Raspberry Pi in real
time. Due to the strong hardware limitations, we decided to not use any
learning algorithms for the obstacle detection part. As it later transpired, a
working "hard coded" software needs thorough analysis and understanding of the
given problem. In layman's terms, we simply seek to make Duckietown a safer
place.