162,130 research outputs found
Algorithms for Moving Objects Databases
@article{DBLP:journals/cj/LemaFGNS03,
author = {Jos{'e} Antonio Cotelo Lema and
Luca Forlizzi and
Ralf Hartmut G{"u}ting and
Enrico Nardelli and
Markus Schneider},
title = {Algorithms for Moving Objects Databases.},
journal = {Comput. J.},
volume = {46},
number = {6},
year = {2003},
pages = {680-712},
ee = {http://www3.oup.co.uk/computer_journal/current/460680.sgm.abs.html},
bibsource = {DBLP, http://dblp.uni-trier.de}
The design of interfaces for multi-robot path planning and control
The field of human-robot interaction has evolved beyond issues concerning the design and development of one person controlling one robot to exploring HRI for groups of robots and teams. Our design research explores biologically-inspired motion that is initiated by a human operator, applied to a single or a small group of robots, and used to affect the motion and path planning of another subset of robots. This exploratory design study first created a taxonomy to categorize individual robot motions, looking at how they could be categorized and used as building blocks. We then combined individual motions with time and velocity as design variables to guide our interaction design. This work led to the development of a prototype set of motions, which was applied in the development of an iPad interface. We informally evaluated this prototype with nine participants. We present challenges and design recommendations based on this effort
A multi-touch interface for multi-robot path planning and control
In the last few years, research in human-robot interaction has moved beyond the issues concerning the design of the interaction between a person and a single robot. Today many researchers have shifted their focus toward the problem of how humans can control a multi-robot team. The rising of multi-touch devices provides a new range of opportunities in this sense. Our research seeks to discover new insights and guidelines for the design of multi-touch interfaces for the control of biologically inspired multi-robot teams. We have developed an iPad touch interface that lets users exert partial control over a set of autonomous robots. The interface also serves as an experimental platform to study how human operators design multi-robot motion in a pursuit-evasion setting
On the stability of approximation for Hamiltonian path problems
@proceedings{DBLP:conf/sofsem/2005,
editor = {Peter Vojt{'a}s and
M{'a}ria Bielikov{'a} and
Bernadette Charron-Bost and
Ondrej S{'y}kora},
title = {SOFSEM 2005: Theory and Practice of Computer Science, 31st
Conference on Current Trends in Theory and Practice of Computer
Science, Liptovsk{'y} J{'a}n, Slovakia, January
22-28, 2005, Proceedings},
booktitle = {SOFSEM},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
volume = {3381},
year = {2005},
isbn = {3-540-24302-X},
bibsource = {DBLP, http://dblp.uni-trier.de}
[Report to Chief J. E. Curry, by an unknown author #1]
Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #2]
Report to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
On the Stability of Approximation for Hamiltonian Path Problems
We consider the problem of finding a cheapest Hamiltonian path of a complete graph satisfying a relaxed triangle
inequality, i.e., such that for some parameter , the edge costs satisfy the inequality
for every triple of vertices , , .
There are three variants of this problem, depending on the number of prespecified endpoints: zero, one, or two.
For metric graphs, there exist approximation algorithms, with approximation ratio for the first two variants
and for the latter one, respectively.
Using results on the approximability of the Travelling Salesman Problem with input graphs satisfying the relaxed triangle inequality,
we obtain for our problem approximation algorithms with ratio for zero or one prespecified endpoints,
and for two endpoints
On the Approximability of TSP on Local Modifications of Optimally Solved Instances
Given an instance of TSP together with an optimal solution, we consider
the scenario in which this instance is modified locally, where a local
modification consists in the alteration of the weight of a single edge.
More generally, for a problem , let \textsc{lm-}U
(local-modification-) denote the same problem as~, but in
\textsc{lm-}U, we are also given an optimal solution to an instance
from which the input instance can be derived by a local modification.
The question is how to exploit this additional knowledge, \ie how to
devise better algorithms for \textsc{lm-}U than for~. Note that
this need not be possible in all cases: The general problem of
\tweakTSP is as hard as \TSP itself, \ie unless , there is no
polynomial-time -approximation algorithm for \tweakTSP for any
polynomial~. Moreover, \tweakTSP where inputs must satisfy the
-triangle inequality (\tweakTSPDB) remains NP-hard for all
.
However, for \tweakTSPD (\ie metric \tweakTSP), we will present an
efficient -approx\-i\-ma\-tion algorithm.
In other words, the additional information enables us to do better
than if we simply used Christofides' algorithm for the modified input.
Similarly, for all , we achieve a
better approximation ratio for \tweakTSPDB than for \TSPDB.
For , we show how to obtain an approximation
ratio arbitrarily close to~, for sufficiently large input graphs
Murder on the mountain: author talk with Peter J. Wosh
Author talk by Peter J. Wosh on May 5th, 2022, on his book, "Murder on the Mountain: crime, passion, and punishment in gilded age New Jersey.
- …
