Evaluating the Robot Inclusivity of Buildings Based on Surface Unevenness Article Swipe
Charan Satya Chandra Sairam Borusu
,
Matthew S. K. Yeo
,
Zimou Zeng
,
M. A. Viraj J. Muthugala
,
Michael Budig
,
Mohan Rajesh Elara
,
Yixiao Wang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/app14177831
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/app14177831
Mobile service robots experience excessive vibrations when travelling over uneven surfaces in their workspace, increasing the degradation rate of the mechanical components or disrupting the robot’s sensing abilities for proper localization and navigational capabilities. Robot inclusivity principles can determine the suitability of a site for robot performance by considering the ground’s unevenness. This paper proposes a novel framework to autonomously evaluate the Robot Inclusivity Level of buildings based on surface unevenness (RIL-SU) by quantifying the surface unevenness of floor surfaces. The surface unevenness values are converted to RIL-SU using a rule-based approach, and the corresponding RIL-SU is tagged to the map location. A coloured heatmap based on the RIL-SU values is created as a visual representation of the RIL-SU of a given space. This heatmap would be useful for modifying the environment to make it more robot-friendly or restrict the robot’s operation in certain areas to avoid possible robot failures. The experimental results show that the proposed framework can successfully generate a valid RIL-SU heatmap for building environments.
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Metadata
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- Landing Page
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- References
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4402242309Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/app14177831Digital Object Identifier
- Title
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Evaluating the Robot Inclusivity of Buildings Based on Surface UnevennessWork title
- Type
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
- Publication date
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2024-09-04Full publication date if available
- Authors
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Charan Satya Chandra Sairam Borusu, Matthew S. K. Yeo, Zimou Zeng, M. A. Viraj J. Muthugala, Michael Budig, Mohan Rajesh Elara, Yixiao WangList of authors in order
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.3390/app14177831Direct OA link when available
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Architectural engineering, Computer science, Environmental science, EngineeringTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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41Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.are | 84 |
| abstract_inverted_index.can | 37, 158 |
| abstract_inverted_index.for | 28, 44, 128, 165 |
| abstract_inverted_index.map | 100 |
| abstract_inverted_index.the | 15, 19, 24, 39, 49, 61, 74, 93, 99, 107, 117, 130, 139, 155 |
| abstract_inverted_index.This | 52, 123 |
| abstract_inverted_index.make | 133 |
| abstract_inverted_index.more | 135 |
| abstract_inverted_index.over | 8 |
| abstract_inverted_index.rate | 17 |
| abstract_inverted_index.show | 153 |
| abstract_inverted_index.site | 43 |
| abstract_inverted_index.that | 154 |
| abstract_inverted_index.when | 6 |
| abstract_inverted_index.Level | 64 |
| abstract_inverted_index.Robot | 34, 62 |
| abstract_inverted_index.areas | 144 |
| abstract_inverted_index.avoid | 146 |
| abstract_inverted_index.based | 67, 105 |
| abstract_inverted_index.floor | 78 |
| abstract_inverted_index.given | 121 |
| abstract_inverted_index.novel | 56 |
| abstract_inverted_index.paper | 53 |
| abstract_inverted_index.robot | 45, 148 |
| abstract_inverted_index.their | 12 |
| abstract_inverted_index.using | 88 |
| abstract_inverted_index.valid | 162 |
| abstract_inverted_index.would | 125 |
| abstract_inverted_index.Mobile | 0 |
| abstract_inverted_index.RIL-SU | 87, 95, 108, 118, 163 |
| abstract_inverted_index.proper | 29 |
| abstract_inverted_index.robots | 2 |
| abstract_inverted_index.space. | 122 |
| abstract_inverted_index.tagged | 97 |
| abstract_inverted_index.uneven | 9 |
| abstract_inverted_index.useful | 127 |
| abstract_inverted_index.values | 83, 109 |
| abstract_inverted_index.visual | 114 |
| abstract_inverted_index.certain | 143 |
| abstract_inverted_index.created | 111 |
| abstract_inverted_index.heatmap | 104, 124, 164 |
| abstract_inverted_index.results | 152 |
| abstract_inverted_index.sensing | 26 |
| abstract_inverted_index.service | 1 |
| abstract_inverted_index.surface | 69, 75, 81 |
| abstract_inverted_index.(RIL-SU) | 71 |
| abstract_inverted_index.building | 166 |
| abstract_inverted_index.coloured | 103 |
| abstract_inverted_index.evaluate | 60 |
| abstract_inverted_index.generate | 160 |
| abstract_inverted_index.possible | 147 |
| abstract_inverted_index.proposed | 156 |
| abstract_inverted_index.proposes | 54 |
| abstract_inverted_index.restrict | 138 |
| abstract_inverted_index.surfaces | 10 |
| abstract_inverted_index.abilities | 27 |
| abstract_inverted_index.approach, | 91 |
| abstract_inverted_index.buildings | 66 |
| abstract_inverted_index.converted | 85 |
| abstract_inverted_index.determine | 38 |
| abstract_inverted_index.excessive | 4 |
| abstract_inverted_index.failures. | 149 |
| abstract_inverted_index.framework | 57, 157 |
| abstract_inverted_index.location. | 101 |
| abstract_inverted_index.modifying | 129 |
| abstract_inverted_index.operation | 141 |
| abstract_inverted_index.robot’s | 25, 140 |
| abstract_inverted_index.surfaces. | 79 |
| abstract_inverted_index.components | 21 |
| abstract_inverted_index.disrupting | 23 |
| abstract_inverted_index.experience | 3 |
| abstract_inverted_index.ground’s | 50 |
| abstract_inverted_index.increasing | 14 |
| abstract_inverted_index.mechanical | 20 |
| abstract_inverted_index.principles | 36 |
| abstract_inverted_index.rule-based | 90 |
| abstract_inverted_index.travelling | 7 |
| abstract_inverted_index.unevenness | 70, 76, 82 |
| abstract_inverted_index.vibrations | 5 |
| abstract_inverted_index.workspace, | 13 |
| abstract_inverted_index.Inclusivity | 63 |
| abstract_inverted_index.considering | 48 |
| abstract_inverted_index.degradation | 16 |
| abstract_inverted_index.environment | 131 |
| abstract_inverted_index.inclusivity | 35 |
| abstract_inverted_index.performance | 46 |
| abstract_inverted_index.quantifying | 73 |
| abstract_inverted_index.suitability | 40 |
| abstract_inverted_index.unevenness. | 51 |
| abstract_inverted_index.autonomously | 59 |
| abstract_inverted_index.experimental | 151 |
| abstract_inverted_index.localization | 30 |
| abstract_inverted_index.navigational | 32 |
| abstract_inverted_index.successfully | 159 |
| abstract_inverted_index.capabilities. | 33 |
| abstract_inverted_index.corresponding | 94 |
| abstract_inverted_index.environments. | 167 |
| abstract_inverted_index.representation | 115 |
| abstract_inverted_index.robot-friendly | 136 |
| cited_by_percentile_year | |
| countries_distinct_count | 2 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.23194473 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |