• Sorted by Date • Classified by Publication Type • Classified by Topic • Grouped by Student (current) • Grouped by Former Students •
Gal A. Kaminka, Ruti Schechter-Glick, and Vladimir Sadov. Using Sensor
Morphology for Multi-Robot Formations. IEEE Transactions on Robotics, pp. 271–282, 2008.
Not all robots are created equal (at least in terms of sensors), and thus must be treated differently when coordinating. We presented a novel representation of the sensing capabilities of robots in formations, which move while maintaining their relative positions in a pre-defined geometric shape. Previous work has examined formation-maintenance algorithms that ensure the theoretical stability of the formation, but often ignored the question of using information about sensor capabilities to increase the robustness of the formation in practice. For each geometric formation, an exponential number of stable controllers exists. Thus a key question is how to select (construct) a formation controller that optimizes desired properties, such as sensor usage for robustness. This paper presents a monitoring multi-graph framework for formation controller selection, based on sensor-morphology considerations. We instantiate the framework, and present two contributions. First, we show that graph-theoretic techniques can then be used to efficiently compute sensing policies that maintain a given formation. In particular, separation-bearing (distance-angle) control laws are automatically constructed for each individual robot in the formation, taking into account its specifically sensor morphology. Second, we present a protocol allowing controllers to be switched on-line, to allow robots to adjust to sensory failures. We report on results from comprehensive experiments with physical robots. The results show that the use of the dynamic protocol allows formations of real robots to move significantly faster and with greater precision, while reducing the number of formation failures, due to sensor limitations.
The article's official web page is at: http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=4481174&arnumber=4472847&count=34&index=4. Movies demonstrating the technique in action can be found at http://www.cs.biu.ac.il/~maverick/Movies/
@Article{tro08,
author = {Gal A. Kaminka and Ruti Schechter-Glick and Vladimir Sadov},
title = {Using Sensor Morphology for Multi-Robot Formations},
journal = {{IEEE} Transactions on Robotics},
year = {2008},
OPTkey = {},
OPTvolume = {},
OPTnumber = {},
pages = {271--282},
OPTmonth = {},
OPTnote = {},
OPTannote = {},
OPTdoi = {http://dx.doi.org/10.1109/TRO.2008.918054},
wwwnote = {},
abstract = {Not all robots are created equal (at least in terms of sensors), and
thus must be treated differently when coordinating. We presented a novel
representation of the sensing capabilities of robots in formations, which move
while maintaining their relative positions in a pre-defined geometric shape.
Previous work has examined formation-maintenance algorithms that ensure
the theoretical stability of the formation, but often ignored the question of
using information about sensor capabilities to increase the robustness of the
formation in practice. For each geometric formation, an exponential number of
stable controllers exists. Thus a key question is how to select (construct) a
formation controller that optimizes desired properties, such as sensor usage for
robustness. This paper presents a monitoring multi-graph framework for
formation controller selection, based on sensor-morphology considerations. We
instantiate the framework, and present two contributions. First, we show that
graph-theoretic techniques can then be used to efficiently compute sensing
policies that maintain a given formation. In particular, separation-bearing
(distance-angle) control laws are automatically constructed for each individual
robot in the formation, taking into account its specifically sensor morphology.
Second, we present a protocol allowing controllers to be switched on-line, to
allow robots to adjust to sensory failures. We report on results from
comprehensive experiments with physical robots. The results show that the use
of the dynamic protocol allows formations of real robots to move significantly
faster and with greater precision, while reducing the number of formation
failures, due to sensor limitations.},
}
Generated by bib2html.pl (written by Patrick Riley ) on Fri Aug 30, 2024 17:29:51