A Path-Planning algorithm based on receding horizon techniques

MURILLO M; SANCHEZ G; GENZELIS, L.; GIOVANINI L

Cordoba

Jornada; IX Jornadas Argentinas de Robótica; 2017

Universidad Tecnologica Nacional, Facultad Regional Córdoba

In this article we present a path-planning algorithm that can be used to generate optimal and feasible paths for any kind of unmanned vehicle (UV). The proposed algorithm is based on the use of a simplified particle vehicle (PV) model, which includes the basic dynamics and constraints of the UV, and an iterated non-linear model predictive control (NMPC) technique that computes the optimal velocity vector (magnitude and orientation angles) that allows the PV to move towards desired targets. The computed paths are guaranteed to be feasible for any UV because: i) the PV is configured with similar characteristics (dynamics and physical constraints) as the UV, and ii) the feasibility of the optimization problem is guaranteed by the use of the iterated NMPC algorithm. As demonstrationof the capabilities of the proposed path-planning algorithm, we explore the computation of a feasible path while following it with a Husky unmanned ground vehicle (UGV) using Gazebo simulator.