Sequential path planning for a formation of mobile robots with split and merge Article Swipe
Maira Estefanía Pereyra
,
Gastón Araguás
,
Miroslav Kulich
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1109/la-cci.2017.8285722
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1109/la-cci.2017.8285722
An algorithm for robot formation path planning is presented in this paper.\nGiven a map of the working environment, the algorithm finds a path for a\nformation taking into account possible split of the formation and its\nconsecutive merge. The key part of the solution works on a graph and\nsequentially employs an extended version of Dijkstra's graph-based algorithm\nfor multiple robots. It is thus deterministic, complete, computationally\ninexpensive, and finds a solution for a fixed source node to another node in\nthe graph. Moreover, the presented solution is general enough to be\nincorporated into high-level tasks like cooperative surveillance and it can\nbenefit from state-of-the-art formation motion planning approaches, which can\nbe used for evaluation of edges of an input graph. The performed experimental\nresults demonstrate the behavior of the method in complex environments for\nformations consisting of tens of robots.\n
Related Topics
Concepts
Merge (version control)
Dijkstra's algorithm
Motion planning
Computer science
Robot
Mobile robot
Any-angle path planning
Graph
Graph traversal
Algorithm
Theoretical computer science
Shortest path problem
Mathematical optimization
Artificial intelligence
Mathematics
Parallel computing
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1109/la-cci.2017.8285722
- OA Status
- green
- Cited By
- 4
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2787371296
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2787371296Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/la-cci.2017.8285722Digital Object Identifier
- Title
-
Sequential path planning for a formation of mobile robots with split and mergeWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2017Year of publication
- Publication date
-
2017-11-01Full publication date if available
- Authors
-
Maira Estefanía Pereyra, Gastón Araguás, Miroslav KulichList of authors in order
- Landing page
-
https://doi.org/10.1109/la-cci.2017.8285722Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1901.08444Direct OA link when available
- Concepts
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Merge (version control), Dijkstra's algorithm, Motion planning, Computer science, Robot, Mobile robot, Any-angle path planning, Graph, Graph traversal, Algorithm, Theoretical computer science, Shortest path problem, Mathematical optimization, Artificial intelligence, Mathematics, Parallel computingTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2022: 1, 2020: 2Per-year citation counts (last 5 years)
- References (count)
-
23Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.for | 2, 23, 67, 104 |
| abstract_inverted_index.key | 37 |
| abstract_inverted_index.map | 13 |
| abstract_inverted_index.the | 15, 18, 31, 40, 78, 116, 119 |
| abstract_inverted_index.from | 95 |
| abstract_inverted_index.into | 26, 86 |
| abstract_inverted_index.like | 89 |
| abstract_inverted_index.node | 71, 74 |
| abstract_inverted_index.part | 38 |
| abstract_inverted_index.path | 5, 22 |
| abstract_inverted_index.tens | 127 |
| abstract_inverted_index.this | 10 |
| abstract_inverted_index.thus | 59 |
| abstract_inverted_index.used | 103 |
| abstract_inverted_index.edges | 107 |
| abstract_inverted_index.finds | 20, 64 |
| abstract_inverted_index.fixed | 69 |
| abstract_inverted_index.graph | 45 |
| abstract_inverted_index.input | 110 |
| abstract_inverted_index.robot | 3 |
| abstract_inverted_index.split | 29 |
| abstract_inverted_index.tasks | 88 |
| abstract_inverted_index.which | 101 |
| abstract_inverted_index.works | 42 |
| abstract_inverted_index.enough | 83 |
| abstract_inverted_index.graph. | 76, 111 |
| abstract_inverted_index.merge. | 35 |
| abstract_inverted_index.method | 120 |
| abstract_inverted_index.motion | 98 |
| abstract_inverted_index.source | 70 |
| abstract_inverted_index.taking | 25 |
| abstract_inverted_index.account | 27 |
| abstract_inverted_index.another | 73 |
| abstract_inverted_index.can\nbe | 102 |
| abstract_inverted_index.complex | 122 |
| abstract_inverted_index.employs | 47 |
| abstract_inverted_index.general | 82 |
| abstract_inverted_index.in\nthe | 75 |
| abstract_inverted_index.robots. | 56 |
| abstract_inverted_index.version | 50 |
| abstract_inverted_index.working | 16 |
| abstract_inverted_index.behavior | 117 |
| abstract_inverted_index.extended | 49 |
| abstract_inverted_index.multiple | 55 |
| abstract_inverted_index.planning | 6, 99 |
| abstract_inverted_index.possible | 28 |
| abstract_inverted_index.solution | 41, 66, 80 |
| abstract_inverted_index.Moreover, | 77 |
| abstract_inverted_index.algorithm | 1, 19 |
| abstract_inverted_index.complete, | 61 |
| abstract_inverted_index.formation | 4, 32, 97 |
| abstract_inverted_index.performed | 113 |
| abstract_inverted_index.presented | 8, 79 |
| abstract_inverted_index.robots.\n | 129 |
| abstract_inverted_index.Dijkstra's | 52 |
| abstract_inverted_index.consisting | 125 |
| abstract_inverted_index.evaluation | 105 |
| abstract_inverted_index.high-level | 87 |
| abstract_inverted_index.approaches, | 100 |
| abstract_inverted_index.cooperative | 90 |
| abstract_inverted_index.demonstrate | 115 |
| abstract_inverted_index.graph-based | 53 |
| abstract_inverted_index.a\nformation | 24 |
| abstract_inverted_index.can\nbenefit | 94 |
| abstract_inverted_index.environment, | 17 |
| abstract_inverted_index.environments | 123 |
| abstract_inverted_index.surveillance | 91 |
| abstract_inverted_index.paper.\nGiven | 11 |
| abstract_inverted_index.algorithm\nfor | 54 |
| abstract_inverted_index.deterministic, | 60 |
| abstract_inverted_index.for\nformations | 124 |
| abstract_inverted_index.be\nincorporated | 85 |
| abstract_inverted_index.its\nconsecutive | 34 |
| abstract_inverted_index.state-of-the-art | 96 |
| abstract_inverted_index.and\nsequentially | 46 |
| abstract_inverted_index.experimental\nresults | 114 |
| abstract_inverted_index.computationally\ninexpensive, | 62 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.60385366 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |