Page 87 - Innovations in Intelligent Machines

UAV Path Planning Using Evolutionary
Algorithms

Ioannis K. Nikolos, Eleftherios S. Zografos, and Athina N. Brintaki

Department of Production Engineering and Management,
Technical University of Crete, University Campus,
Kounoupidiana, GR-73100, Chania, Greece
jnikolo@dpem.tuc.gr

Abstract. Evolutionary Algorithms have been used as a viable candidate to solve
path planning problems effectively and provide feasible solutions within a short time.
In this work a Radial Basis Functions Artificial Neural Network (RBF-ANN) assisted
Differential Evolution (DE) algorithm is used to design an off-line path planner for
Unmanned Aerial Vehicles (UAVs) coordinated navigation in known static maritime
environments. A number of UAVs are launched from different known initial locations
and the issue is to produce 2-D trajectories, with a smooth velocity distribution along
each trajectory, aiming at reaching a predetermined target location, while ensuring
collision avoidance and satisfying specific route and coordination constraints and
objectives. B-Spline curves are used, in order to model both the 2-D trajectories
and the velocity distribution along each flight path.

1 Introduction

1.1 Basic Definitions

The term unmanned aerial vehicle or UAV, which replaced in the early 1990s
the term remotely piloted vehicle (RPV), refers to a powered aerial vehicle
that does not carry a human operator, uses aerodynamic forces to provide
vehicle lift, can fly autonomously or be piloted remotely, can be expendable
or recoverable, and can carry a lethal or non lethal payload [1]. UAVs are
currently evolving from being remotely piloted vehicles to autonomous robots,
although ultimate autonomy is still an open question.
The development of autonomous robots is one of the major goals in Robot-
ics [2]. Such robots will be capable of converting high-level specification of
tasks, defined by humans, to low-level action algorithms, which will be exe-
cuted in order to accomplish the predefined tasks. We may define as plan this
sequence of actions to be taken, although it may be much more complicated
than that. Motion planning (or trajectory planning) is one category of such

I.K. Nikolos et al.: UAV Path Planning Using Evolutionary Algorithms, Studies in Computa-
tional Intelligence (SCI) 70, 77–111 (2007)
www.springerlink.com c Springer-Verlag Berlin Heidelberg 2007