TY - JOUR
T1 - An Euclidean norm based criterion to assess robots' 2D
path-following performance
AU - Saggini, Eleonora
AU - Torrente, Maria Laura
PY - 2016
Y1 - 2016
N2 - A current need in the robotics eld is the denition of methodologies for quantitatively
evaluating the results of experiments. This paper contributes to this by dening 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 dierential 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 dened. Based on this,
new algorithms are presented and tested on both simulated data and experiments conducted at
sea employing an Unmanned Surface Vehicle.
AB - A current need in the robotics eld is the denition of methodologies for quantitatively
evaluating the results of experiments. This paper contributes to this by dening 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 dierential 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 dened. Based on this,
new algorithms are presented and tested on both simulated data and experiments conducted at
sea employing an Unmanned Surface Vehicle.
KW - Euclidean norm,Weighted matrix norm, Crossing algorithm, Robotics, Good experimental methodologies, Path-following
KW - Euclidean norm,Weighted matrix norm, Crossing algorithm, Robotics, Good experimental methodologies, Path-following
UR - http://hdl.handle.net/10807/85671
M3 - Article
SP - 45
EP - 71
JO - JOURNAL OF ALGEBRAIC STATISTICS
JF - JOURNAL OF ALGEBRAIC STATISTICS
SN - 1309-3452
ER -