Gal A. Kaminka's Publications

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On Redundancy, Efficiency, and Robustness in Coverage for Multiple Robots

Noam Hazon and Gal Kaminka. On Redundancy, Efficiency, and Robustness in Coverage for Multiple Robots . Robotics and Autonomous Systems, 56(12):1102–1114, 2008.

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Abstract

Motivated by potential efficiency and robustness gains, there is growing interest in the use of multiple robots for coverage. In coverage, robots visit every point in a target area, at least once. Previous investigations of multi-robot coverage focus on completeness of the coverage, and on eliminating redundancy, but do not formally address robustness. Moreover, a common assumption is that elimination of redundancy leads to improved efficiency (coverage time). We address robustness and efficiency in a novel family of multi-robot coverage algorithms, based on spanning-tree coverage of approximate cell decomposition of the work area. We analytically show that the algorithms are robust, in that as long as a single robot is able to move, the coverage will be completed. We also show that non-redundant (non-backtracking) versions of the algorithms have a worst-case coverage time virtually identical to that of a single robot---thus no performance gain is guaranteed in non-redundant coverage. Surprisingly, however, redundant coverage algorithms lead to guaranteed performance which halves the coverage time even in the worst case. We present a polynomial-time redundant-coverage algorithm, whose coverage time is optimal, and which is able to address robots heterogeneous in speed and fuel. We compare the performance of all algorithms empirically and show that use of the optimal algorithm leads to significant improvements in coverage time.

BibTeX

@Article{ras08,
 author = {Noam Hazon and Gal Kaminka},
 title = {On Redundancy, Efficiency, and Robustness in Coverage for Multiple Robots },
 journal = {Robotics and Autonomous Systems},
 year = {2008},
 OPTkey = {},
 volume = {56},
 number = {12},
 pages = {1102--1114},
 OPTmonth = {December},
 OPTnote = {},
  wwwnote = {}, 
abstract = {
Motivated by potential efficiency and robustness gains, there is growing interest in the use of 
multiple robots for \emph{coverage}. In coverage, robots visit every point in a target 
area, at least once.  Previous investigations of multi-robot 
coverage focus on completeness of the coverage, and on eliminating redundancy, but do 
not formally address robustness. Moreover, a common assumption 
is that elimination of redundancy leads to improved efficiency (coverage time). We address 
robustness and efficiency in a novel family of multi-robot coverage 
algorithms, based on spanning-tree coverage of approximate cell 
decomposition of the work area. We analytically show that the algorithms are robust, 
in that as long as a single robot is able to move, the coverage will 
be completed.  We also show that non-redundant (non-backtracking) 
versions of the algorithms have a worst-case coverage time virtually 
identical to that of a single robot---thus no performance gain is 
guaranteed in non-redundant coverage. Surprisingly, however, 
redundant coverage algorithms lead to guaranteed performance which 
halves the coverage time even in the worst case. We present a polynomial-time 
redundant-coverage algorithm, whose coverage time is optimal, and which is 
able to address robots heterogeneous in speed and fuel. We compare the performance 
of all algorithms empirically and show that use of the optimal algorithm leads 
to significant improvements in coverage time. }, 
OPTannote = {}
}

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