Performance analysis of path planners for car-like vehicles toward automatic parking control

Abstract

Acar parking control problem is difficult because of its non-holonomic constraints and complicated environmental geometry. We proposed Korea University Path Planner (KPP) in our prior work. KPP is an appropriate scheme for a car-like mobile robot in a parking environment. The purpose of this paper is to investigate the advantages of KPP through both quantitative and qualitative analyses. For comparison, numerical simulations have been carried out by the application of KPP and the conventional Rapidly exploring random tree method. This paper shows that KPP exhibits outstanding performance from the viewpoints of travel time and computational time.