On redundancy, efficiency, and robustness in coverage for multiple robots

Hazon, Noam; Kaminka, Gal A.

doi:10.1016/j.robot.2008.01.006

Cited by 113 publications

(68 citation statements)

References 19 publications

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“…Our approach partly builds on the work of Hazon and Kaminka (2008). They extended the single-robot off-line spanning-tree coverage algorithm by Gabriely and Rimon (2001) to the use of multiple robots and addressed robustness and efficiency.…”

Section: Related Workmentioning

confidence: 99%

Multi-robot Coverage Considering Line-of-sight Conditions

Hofmeister

Kronfeld

2010

IFAC Proceedings Volumes

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In this paper, we present a novel approach to the area coverage problem by using a team of heterogeneous mobile robots. In our method, a parent robot is assumed to possess state-of-the-art sensors and sufficient computation power to establish robust localization and navigation. A large number of inexpensive and small child robots possess only restricted sensing and computation capabilities. They can only fulfill a certain task, e.g., floor-cleaning, but can be teleoperated in line-of-sight of the parent robot. To exploit the advantages of both types of robots, the team cooperatively covers the area in an efficient way. In contrast to other approaches and due to the cooperation of the robots, we can relax the requirement that every robot must be able to self-localize and robustly navigate to take part in efficient multi-robot coverage. Simulation results are presented in which our approach was tested intensively.

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Section: Related Workmentioning

confidence: 99%

Multi-robot Coverage Considering Line-of-sight Conditions

Hofmeister

Kronfeld

2010

IFAC Proceedings Volumes

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“…The proof will built upon a polynomial reduction from an arbitrary instance of a well-known N P-hard problem, namely the Euclidean-TSP (ETSP) to a special instance of MTUSP 4 .…”

Section: Remark 2 (Variations)mentioning

confidence: 99%

“…We will now discuss each of these categories in more detail. In the first category, where sensor range is the main limitation on the extension of the visible area we find problems such as vacuum cleaning and demining, [1,2], general coverage [3][4][5], multi robot coverage [6] and some robotic security applications [7]. Furthermore, a number of UAV surveillance papers, such as [8][9][10] fall into this category.…”

Section: Introductionmentioning

confidence: 99%

Minimum Time Multi-UGV Surveillance

Anisi

Ögren

2009

Optimization and Cooperative Control Strategies

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Abstract. This chapter addresses the problem of concurrent task and path planning for a number of surveillance Unmanned Ground Vehicles (UGVs) such that a user defined area of interest is covered by the UGVs' sensors in minimum time. We first formulate the problem, and show that it is in fact a generalization of the Multiple Traveling Salesmen Problem (MTSP), which is known to be N P-hard. We then propose a solution that decomposes the problem into three subproblems. The first is to find a maximal convex covering of the search area. Most results on static coverage use disjoint partitions of the search area, e.g., triangulation, to convert the continuous sensor positioning problem into a discrete one. However, by a simple example, we show that a highly overlapping set of maximal convex sets is better suited for minimum time coverage. The second subproblem is a combinatorial assignment and ordering of the sets in the cover. Since the Tabu search algorithm is known to perform well on various routing problems, we use it as a part of our proposed solution. Finally, the third subproblem utilizes a particular shortest path subroutine in order to find the vehicle paths, and calculate the overall objective function used in the Tabu search. The proposed algorithm is illustrated by a number of simulation examples.

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“…• Single Coverage: The aim is to cover the target area until all the accessible points of interest in the environment have been visited at least once, while minimizing the time, distance traversed by the robots, and the number of visits to the points (Fazli et al 2010a,b;Hazon and Kaminka 2008;Rekleitis et al 2008). …”

Section: Introductionmentioning

confidence: 99%

Multi-robot repeated area coverage

2013

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We address the problem of repeated coverage of a target area, of any polygonal shape, by a team of robots having a limited visual range. Three distributed Clusterbased algorithms, and a method called Cyclic Coverage are introduced for the problem. The goal is to evaluate the performance of the repeated coverage algorithms under the effects of the variables: Environment Representation, and the Robots' Visual Range. A comprehensive set of performance metrics are considered, including the distance the robots travel, the frequency of visiting points in the target area, and the degree of balance in workload distribution among the robots. The Cyclic Coverage approach, used as a benchmark to compare the algorithms, produces optimal or near-optimal solutions for the single robot case under some criteria. The results can be used as a framework for choosing an appropriate combination of repeated coverage algorithm, environment representation, and the robots' visual range based on the particular scenario and the metric to be optimized.

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On redundancy, efficiency, and robustness in coverage for multiple robots

Cited by 113 publications

References 19 publications

Multi-robot Coverage Considering Line-of-sight Conditions

Multi-robot Coverage Considering Line-of-sight Conditions

Minimum Time Multi-UGV Surveillance

Multi-robot repeated area coverage

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