Efficient and Safe Robotic Autonomous Environment Exploration Using Integrated Frontier Detection and Multiple Path Evaluation Article Swipe
Autonomous exploration and remote sensing using robots have gained increasing attention in recent years and aims to maximize information collection regarding the external world without human intervention. However, incomplete frontier detection, an inability to eliminate inefficient frontiers, and incomplete evaluation limit further improvements in autonomous exploration efficiency. This article provides a systematic solution for ground mobile robot exploration with high efficiency. Firstly, an integrated frontier detection and maintenance method is proposed, which incrementally discovers potential frontiers and achieves incremental maintenance of the safe and informative frontiers by updating the distance map locally. Secondly, we propose a novel multiple paths planning method to generate multiple paths from the robot position to the unexplored frontiers. Then, we use the proposed utility function to select the optimal path and improve its smoothness using an iterative optimization strategy. Ultimately, the model predictive control (MPC) method is applied to track the smooth path. Simulation experiments on typical environments demonstrate that compared with the benchmark methods, the proposed method reduce the path length by 27.07% and the exploration time by 27.09% on average. The real-world experimental results also reveal that our proposed method can achieve complete mapping with fewer repetitive paths.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/rs13234881
- https://www.mdpi.com/2072-4292/13/23/4881/pdf?version=1638362772
- OA Status
- gold
- Cited By
- 9
- References
- 53
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3217015082
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3217015082Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/rs13234881Digital Object Identifier
- Title
-
Efficient and Safe Robotic Autonomous Environment Exploration Using Integrated Frontier Detection and Multiple Path EvaluationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-12-01Full publication date if available
- Authors
-
Yuxi Sun, Chengrui ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/rs13234881Publisher landing page
- PDF URL
-
https://www.mdpi.com/2072-4292/13/23/4881/pdf?version=1638362772Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2072-4292/13/23/4881/pdf?version=1638362772Direct OA link when available
- Concepts
-
Computer science, Benchmark (surveying), Motion planning, Path (computing), Robot, Artificial intelligence, Real-time computing, Geography, Geodesy, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
9Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 2, 2023: 1, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
53Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.the | 21, 81, 88, 106, 110, 116, 122, 135, 145, 157, 160, 164, 170 |
| abstract_inverted_index.use | 115 |
| abstract_inverted_index.This | 47 |
| abstract_inverted_index.aims | 15 |
| abstract_inverted_index.also | 181 |
| abstract_inverted_index.from | 105 |
| abstract_inverted_index.have | 7 |
| abstract_inverted_index.high | 59 |
| abstract_inverted_index.path | 124, 165 |
| abstract_inverted_index.safe | 82 |
| abstract_inverted_index.that | 154, 183 |
| abstract_inverted_index.time | 172 |
| abstract_inverted_index.with | 58, 156, 191 |
| abstract_inverted_index.(MPC) | 139 |
| abstract_inverted_index.Then, | 113 |
| abstract_inverted_index.fewer | 192 |
| abstract_inverted_index.human | 25 |
| abstract_inverted_index.limit | 40 |
| abstract_inverted_index.model | 136 |
| abstract_inverted_index.novel | 96 |
| abstract_inverted_index.path. | 147 |
| abstract_inverted_index.paths | 98, 104 |
| abstract_inverted_index.robot | 56, 107 |
| abstract_inverted_index.track | 144 |
| abstract_inverted_index.using | 5, 129 |
| abstract_inverted_index.which | 71 |
| abstract_inverted_index.world | 23 |
| abstract_inverted_index.years | 13 |
| abstract_inverted_index.27.07% | 168 |
| abstract_inverted_index.27.09% | 174 |
| abstract_inverted_index.gained | 8 |
| abstract_inverted_index.ground | 54 |
| abstract_inverted_index.length | 166 |
| abstract_inverted_index.method | 68, 100, 140, 162, 186 |
| abstract_inverted_index.mobile | 55 |
| abstract_inverted_index.paths. | 194 |
| abstract_inverted_index.recent | 12 |
| abstract_inverted_index.reduce | 163 |
| abstract_inverted_index.remote | 3 |
| abstract_inverted_index.reveal | 182 |
| abstract_inverted_index.robots | 6 |
| abstract_inverted_index.select | 121 |
| abstract_inverted_index.smooth | 146 |
| abstract_inverted_index.achieve | 188 |
| abstract_inverted_index.applied | 142 |
| abstract_inverted_index.article | 48 |
| abstract_inverted_index.control | 138 |
| abstract_inverted_index.further | 41 |
| abstract_inverted_index.improve | 126 |
| abstract_inverted_index.mapping | 190 |
| abstract_inverted_index.optimal | 123 |
| abstract_inverted_index.propose | 94 |
| abstract_inverted_index.results | 180 |
| abstract_inverted_index.sensing | 4 |
| abstract_inverted_index.typical | 151 |
| abstract_inverted_index.utility | 118 |
| abstract_inverted_index.without | 24 |
| abstract_inverted_index.Firstly, | 61 |
| abstract_inverted_index.However, | 27 |
| abstract_inverted_index.achieves | 77 |
| abstract_inverted_index.average. | 176 |
| abstract_inverted_index.compared | 155 |
| abstract_inverted_index.complete | 189 |
| abstract_inverted_index.distance | 89 |
| abstract_inverted_index.external | 22 |
| abstract_inverted_index.frontier | 29, 64 |
| abstract_inverted_index.function | 119 |
| abstract_inverted_index.generate | 102 |
| abstract_inverted_index.locally. | 91 |
| abstract_inverted_index.maximize | 17 |
| abstract_inverted_index.methods, | 159 |
| abstract_inverted_index.multiple | 97, 103 |
| abstract_inverted_index.planning | 99 |
| abstract_inverted_index.position | 108 |
| abstract_inverted_index.proposed | 117, 161, 185 |
| abstract_inverted_index.provides | 49 |
| abstract_inverted_index.solution | 52 |
| abstract_inverted_index.updating | 87 |
| abstract_inverted_index.Secondly, | 92 |
| abstract_inverted_index.attention | 10 |
| abstract_inverted_index.benchmark | 158 |
| abstract_inverted_index.detection | 65 |
| abstract_inverted_index.discovers | 73 |
| abstract_inverted_index.eliminate | 34 |
| abstract_inverted_index.frontiers | 75, 85 |
| abstract_inverted_index.inability | 32 |
| abstract_inverted_index.iterative | 131 |
| abstract_inverted_index.potential | 74 |
| abstract_inverted_index.proposed, | 70 |
| abstract_inverted_index.regarding | 20 |
| abstract_inverted_index.strategy. | 133 |
| abstract_inverted_index.Autonomous | 0 |
| abstract_inverted_index.Simulation | 148 |
| abstract_inverted_index.autonomous | 44 |
| abstract_inverted_index.collection | 19 |
| abstract_inverted_index.detection, | 30 |
| abstract_inverted_index.evaluation | 39 |
| abstract_inverted_index.frontiers, | 36 |
| abstract_inverted_index.frontiers. | 112 |
| abstract_inverted_index.incomplete | 28, 38 |
| abstract_inverted_index.increasing | 9 |
| abstract_inverted_index.integrated | 63 |
| abstract_inverted_index.predictive | 137 |
| abstract_inverted_index.real-world | 178 |
| abstract_inverted_index.repetitive | 193 |
| abstract_inverted_index.smoothness | 128 |
| abstract_inverted_index.systematic | 51 |
| abstract_inverted_index.unexplored | 111 |
| abstract_inverted_index.Ultimately, | 134 |
| abstract_inverted_index.demonstrate | 153 |
| abstract_inverted_index.efficiency. | 46, 60 |
| abstract_inverted_index.experiments | 149 |
| abstract_inverted_index.exploration | 1, 45, 57, 171 |
| abstract_inverted_index.incremental | 78 |
| abstract_inverted_index.inefficient | 35 |
| abstract_inverted_index.information | 18 |
| abstract_inverted_index.informative | 84 |
| abstract_inverted_index.maintenance | 67, 79 |
| abstract_inverted_index.environments | 152 |
| abstract_inverted_index.experimental | 179 |
| abstract_inverted_index.improvements | 42 |
| abstract_inverted_index.optimization | 132 |
| abstract_inverted_index.incrementally | 72 |
| abstract_inverted_index.intervention. | 26 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5077452145 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I154099455 |
| citation_normalized_percentile.value | 0.63432859 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |