Visual collision avoidance by segmentation
Ian Douglas Horswill · 2002
Visual collision avoidance involves two difficult subproblems: obstacle recognition and depth measurement. We present a class of algorithms that use particularly simple methods for each subproblem and derive a set of sufficient conditions for their proper functioning based on a set of idealizations. We then discuss and compare two different implementations of the approach on mobile robots and discuss their performance. Finally, we experimentally validate the idealizations.>