Collision Avoidance for Bi-Steerable Car Using Analytic Left Inversion

Abstract

A case study is presented of a collision avoidance system that directly integrates the kinematics of a bi-steerable car with a suitable path planning algorithm. The first step is to identify a path using the method of rapidly exploring random trees, and then a spline approximation is computed. The second step is to solve the output tracking problem by explicitly computing the left inverse of the kinematics of the system to render the Taylor series of the desired input for each polynomial section of the spline approximation. The method is demonstrated by numerical simulation.