Fuzzy logic based speed planning for autonomous navigation under Velocity Field Control

Abstract

Velocity fields techniques are often used in the path planning and control problem in autonomous navigation. Velocity fields are compounded by vectors that can be expressed in polar form, i.e. V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> = |Voarr| ldr cos(alpha) and V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">y</sub> = |Voarr| ldr sin(alpha). In the proposed technique, the problem is divided into two separate problems: the calculation of the orientation angle alpha, which was treated in a previous work, and the calculation of the linear velocity |Voarr|. This paper addresses the calculation of |Voarr| given a trajectory vector field that encodes alpha, thus generating the speed reference for a Velocity Field Controller. The linear velocity |Voarr| is generated through a Mamdani-type Fuzzy Inference System, that considers the curl of the trajectory vector field, and an extension of the Voronoi Diagram. Results obtained in both simulations and tests with a real robot show that an adequate intelligent velocity behavior, and a smooth obstacle avoidance are achieved.