Towards Narrowing the Search in Bounded-Suboptimal Safe Interval Path Planning Article Swipe
YOU?
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· 2021
· Open Access
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· DOI: https://doi.org/10.1609/socs.v12i1.18562
Path planning in the presence of dynamic obstacles is challenging as the time dimension has to be considered. A prominent approach to tackle this problem known to be complete and optimal is the A*-based Safe-interval Path Planning (SIPP). Bounded-suboptimal variants of SIPP employing the ideas of Weighted A* (WSIPP) and Focal Search (FocalSIPP) have been introduced recently, trading-off optimality for decreased planning time. In this paper, we revisit FocalSIPP and design several secondary heuristics for Focal Search with the intention to narrow the search in the direction of a preplanned optimal single-agent path not considering dynamic obstacles. The experimental results on various maps show that the designed heuristics generally outperform the hops-to-the-goal heuristic used in the original FocalSIPP and successfully compete with WSIPP as well.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/socs.v12i1.18562
- https://ojs.aaai.org/index.php/SOCS/article/download/18562/18351
- OA Status
- diamond
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3196414818
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3196414818Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1609/socs.v12i1.18562Digital Object Identifier
- Title
-
Towards Narrowing the Search in Bounded-Suboptimal Safe Interval Path PlanningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-07-21Full publication date if available
- Authors
-
Tomáš Rybecký, Miroslav Kulich, Anton Andreychuk, Konstantin YakovlevList of authors in order
- Landing page
-
https://doi.org/10.1609/socs.v12i1.18562Publisher landing page
- PDF URL
-
https://ojs.aaai.org/index.php/SOCS/article/download/18562/18351Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://ojs.aaai.org/index.php/SOCS/article/download/18562/18351Direct OA link when available
- Concepts
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Heuristics, Interval (graph theory), Mathematical optimization, Path (computing), Bounded function, Motion planning, Heuristic, Dimension (graph theory), Computer science, Critical path method, Any-angle path planning, Algorithm, Mathematics, Artificial intelligence, Engineering, Combinatorics, Programming language, Robot, Mathematical analysis, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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23Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W6762652492, https://openalex.org/W6685290738, https://openalex.org/W1969483458, https://openalex.org/W6676804497, https://openalex.org/W6683620479, https://openalex.org/W6636254016, https://openalex.org/W1971648593, https://openalex.org/W6660982047, https://openalex.org/W2168424616, https://openalex.org/W6659469833, https://openalex.org/W2949992533, https://openalex.org/W6632792665, https://openalex.org/W3033206061, https://openalex.org/W2735867883, https://openalex.org/W2965850033, https://openalex.org/W1614580925, https://openalex.org/W2035601288, https://openalex.org/W4285092328, https://openalex.org/W2042872950, https://openalex.org/W3038043697, https://openalex.org/W2161076907, https://openalex.org/W2293367869, https://openalex.org/W2113256452 |
| referenced_works_count | 23 |
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| abstract_inverted_index.Bounded-suboptimal | 38 |
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| countries_distinct_count | 2 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.1029453 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |