Matches in SemOpenAlex for { <https://semopenalex.org/work/W3044932790> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3044932790 endingPage "5912" @default.
- W3044932790 startingPage "5905" @default.
- W3044932790 abstract "This letter deals with the problem of multiple robots working together to explore and gather at the global maximum of the unknown field. Given noisy sensor measurements obtained at the location of robots with no prior knowledge about the environmental map, Gaussian process regression can be an efficient solution to construct a map that represents spatial information with confidence intervals. However, because the conventional Gaussian process algorithm operates in a centralized manner, it is difficult to process information coming from multiple distributed sensors in real-time. In this work, we propose a multi-robot exploration algorithm that deals with the following challenges: i) distributed environmental map construction using networked sensing platforms; ii) online learning using successive measurements suitable for a multi-robot team; iii) multi-agent coordination to discover the highest peak of an unknown environmental field with collision avoidance. We demonstrate the effectiveness of our algorithm via simulation and a topographic survey experiment with multiple UAVs." @default.
- W3044932790 created "2020-07-29" @default.
- W3044932790 creator A5006612677 @default.
- W3044932790 creator A5043694287 @default.
- W3044932790 creator A5055716467 @default.
- W3044932790 creator A5073996122 @default.
- W3044932790 creator A5088989913 @default.
- W3044932790 date "2020-10-01" @default.
- W3044932790 modified "2023-09-30" @default.
- W3044932790 title "Multi-Robot Active Sensing and Environmental Model Learning With Distributed Gaussian Process" @default.
- W3044932790 cites W1492251543 @default.
- W3044932790 cites W1864806140 @default.
- W3044932790 cites W2018705428 @default.
- W3044932790 cites W2029443449 @default.
- W3044932790 cites W2044079487 @default.
- W3044932790 cites W2099700272 @default.
- W3044932790 cites W2119333483 @default.
- W3044932790 cites W2129693162 @default.
- W3044932790 cites W2132688592 @default.
- W3044932790 cites W2153263933 @default.
- W3044932790 cites W2164522996 @default.
- W3044932790 cites W2165744313 @default.
- W3044932790 cites W2251608823 @default.
- W3044932790 cites W2415731567 @default.
- W3044932790 cites W2465297489 @default.
- W3044932790 cites W2735099849 @default.
- W3044932790 cites W2949060325 @default.
- W3044932790 cites W2964345570 @default.
- W3044932790 cites W3104558707 @default.
- W3044932790 doi "https://doi.org/10.1109/lra.2020.3010456" @default.
- W3044932790 hasPublicationYear "2020" @default.
- W3044932790 type Work @default.
- W3044932790 sameAs 3044932790 @default.
- W3044932790 citedByCount "24" @default.
- W3044932790 countsByYear W30449327902020 @default.
- W3044932790 countsByYear W30449327902021 @default.
- W3044932790 countsByYear W30449327902022 @default.
- W3044932790 countsByYear W30449327902023 @default.
- W3044932790 crossrefType "journal-article" @default.
- W3044932790 hasAuthorship W3044932790A5006612677 @default.
- W3044932790 hasAuthorship W3044932790A5043694287 @default.
- W3044932790 hasAuthorship W3044932790A5055716467 @default.
- W3044932790 hasAuthorship W3044932790A5073996122 @default.
- W3044932790 hasAuthorship W3044932790A5088989913 @default.
- W3044932790 hasConcept C107457646 @default.
- W3044932790 hasConcept C111919701 @default.
- W3044932790 hasConcept C121332964 @default.
- W3044932790 hasConcept C127313418 @default.
- W3044932790 hasConcept C154945302 @default.
- W3044932790 hasConcept C163716315 @default.
- W3044932790 hasConcept C39432304 @default.
- W3044932790 hasConcept C41008148 @default.
- W3044932790 hasConcept C61326573 @default.
- W3044932790 hasConcept C62520636 @default.
- W3044932790 hasConcept C62649853 @default.
- W3044932790 hasConcept C90509273 @default.
- W3044932790 hasConcept C98045186 @default.
- W3044932790 hasConceptScore W3044932790C107457646 @default.
- W3044932790 hasConceptScore W3044932790C111919701 @default.
- W3044932790 hasConceptScore W3044932790C121332964 @default.
- W3044932790 hasConceptScore W3044932790C127313418 @default.
- W3044932790 hasConceptScore W3044932790C154945302 @default.
- W3044932790 hasConceptScore W3044932790C163716315 @default.
- W3044932790 hasConceptScore W3044932790C39432304 @default.
- W3044932790 hasConceptScore W3044932790C41008148 @default.
- W3044932790 hasConceptScore W3044932790C61326573 @default.
- W3044932790 hasConceptScore W3044932790C62520636 @default.
- W3044932790 hasConceptScore W3044932790C62649853 @default.
- W3044932790 hasConceptScore W3044932790C90509273 @default.
- W3044932790 hasConceptScore W3044932790C98045186 @default.
- W3044932790 hasIssue "4" @default.
- W3044932790 hasLocation W30449327901 @default.
- W3044932790 hasOpenAccess W3044932790 @default.
- W3044932790 hasPrimaryLocation W30449327901 @default.
- W3044932790 hasRelatedWork W1975591846 @default.
- W3044932790 hasRelatedWork W2014322580 @default.
- W3044932790 hasRelatedWork W2026800644 @default.
- W3044932790 hasRelatedWork W2037995797 @default.
- W3044932790 hasRelatedWork W2045456578 @default.
- W3044932790 hasRelatedWork W2076610045 @default.
- W3044932790 hasRelatedWork W2379162918 @default.
- W3044932790 hasRelatedWork W2899084033 @default.
- W3044932790 hasRelatedWork W2918883224 @default.
- W3044932790 hasRelatedWork W4312091514 @default.
- W3044932790 hasVolume "5" @default.
- W3044932790 isParatext "false" @default.
- W3044932790 isRetracted "false" @default.
- W3044932790 magId "3044932790" @default.
- W3044932790 workType "article" @default.