An Euclidean norm based criterion to assess robots’ 2D path-following performance
Author(s) -
Eleonora Saggini,
Maria-Laura Torrente
Publication year - 2016
Publication title -
journal of algebraic statistics
Language(s) - English
Resource type - Journals
ISSN - 1309-3452
DOI - 10.18409/jas.v7i1.48
Subject(s) - robotics , euclidean geometry , robot , euclidean distance , computer science , path (computing) , planar , mathematical optimization , mathematics , artificial intelligence , algorithm , geometry , programming language , computer graphics (images)
A current need in the robotics field is the definition of methodologies for quantitatively evaluating the results of experiments. This paper contributes to this by defining a new criterion for assessing path-following tasks in the planar case, that is, evaluating the performance of robots that are required to follow a desired reference path. Such criterion comes from the study of the local differential geometry of the problem. New conditions for deciding whether or not the zero locus of a given polynomial intersects the neighbourhood of a point are defined. Based on this, new algorithms are presented and tested on both simulated data and experiments conducted at sea employing an Unmanned Surface Vehicle.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom