Sampling based motion planning of Ackermann steering system using transformation

The objective of this work is to apply sampling based algorithm to generate a path to Ackermann steering system with given constraints based on its Kinematics model. Rapidly-exploring Random Tree (RRT) is used with uniform sampling for path exploration. The configuration space is transformed and will be used for path formulation. This paper presents Gaussian sampling based strategy, path formulation meeting system kinematics, and trajectories creation over the sample points.