Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing
In this paper, we present a methodology that uses an optical tactile sensor for efficient tactile exploration of embedded objects within soft materials. The methodology consists of an exploration phase, where a probabilistic estimate of the location of the embedded objects is built using a Bayesian...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Springer Science and Business Media LLC
2024
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| Online Access: | https://hdl.handle.net/1721.1/154045 |
| _version_ | 1824458462596169728 |
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| author | Solano-Castellanos, Jose A. Do, Won Kyung Kennedy, Monroe D. |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Solano-Castellanos, Jose A. Do, Won Kyung Kennedy, Monroe D. |
| author_sort | Solano-Castellanos, Jose A. |
| collection | MIT |
| description | In this paper, we present a methodology that uses an optical tactile sensor for efficient tactile exploration of embedded objects within soft materials. The methodology consists of an exploration phase, where a probabilistic estimate of the location of the embedded objects is built using a Bayesian approach. The exploration phase is then followed by a mapping phase which exploits the probabilistic map to reconstruct the underlying topography of the workspace by sampling in more detail regions where there are expected to be embedded objects. To demonstrate the effectiveness of the method, we tested our approach on an experimental setup that consists of a series of quartz beads located underneath a polyethylene foam that prevents direct observation of the configuration and requires the use of tactile exploration to recover the location of the beads. We show the performance of our methodology using ten different configurations of the beads where the proposed approach is able to approximate the underlying configuration. We benchmark our results against a random sampling policy. Our empirical results show that our method outperforms the fully random policy in both the exploration and mapping phases. The exploration phase produces a better probabilistic map with fewer samples which enables an earlier transition to the mapping phase to reconstruct the underlying shape. On both the exploration and mapping phases, our proposed method presents a better consistency as compared to the random policy, with smaller standard deviation across the ten different bead configurations. |
| first_indexed | 2024-09-23T17:01:52Z |
| format | Article |
| id | mit-1721.1/154045 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:26:17Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1540452025-01-01T04:14:54Z Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing Solano-Castellanos, Jose A. Do, Won Kyung Kennedy, Monroe D. Massachusetts Institute of Technology. Department of Mechanical Engineering Computer Science Applications Computer Networks and Communications Computer Graphics and Computer-Aided Design Computational Theory and Mathematics Artificial Intelligence General Computer Science In this paper, we present a methodology that uses an optical tactile sensor for efficient tactile exploration of embedded objects within soft materials. The methodology consists of an exploration phase, where a probabilistic estimate of the location of the embedded objects is built using a Bayesian approach. The exploration phase is then followed by a mapping phase which exploits the probabilistic map to reconstruct the underlying topography of the workspace by sampling in more detail regions where there are expected to be embedded objects. To demonstrate the effectiveness of the method, we tested our approach on an experimental setup that consists of a series of quartz beads located underneath a polyethylene foam that prevents direct observation of the configuration and requires the use of tactile exploration to recover the location of the beads. We show the performance of our methodology using ten different configurations of the beads where the proposed approach is able to approximate the underlying configuration. We benchmark our results against a random sampling policy. Our empirical results show that our method outperforms the fully random policy in both the exploration and mapping phases. The exploration phase produces a better probabilistic map with fewer samples which enables an earlier transition to the mapping phase to reconstruct the underlying shape. On both the exploration and mapping phases, our proposed method presents a better consistency as compared to the random policy, with smaller standard deviation across the ten different bead configurations. 2024-04-02T17:38:06Z 2024-04-02T17:38:06Z 2024-03-29 2024-03-31T03:17:42Z Article http://purl.org/eprint/type/JournalArticle 2661-8907 https://hdl.handle.net/1721.1/154045 SN Computer Science. 2024 Mar 29;5(4):372 PUBLISHER_CC en 10.1007/s42979-024-02731-6 SN Computer Science Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Science and Business Media LLC Springer Nature Singapore |
| spellingShingle | Computer Science Applications Computer Networks and Communications Computer Graphics and Computer-Aided Design Computational Theory and Mathematics Artificial Intelligence General Computer Science Solano-Castellanos, Jose A. Do, Won Kyung Kennedy, Monroe D. Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing |
| title | Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing |
| title_full | Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing |
| title_fullStr | Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing |
| title_full_unstemmed | Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing |
| title_short | Embedded Object Detection and Mapping in Soft Materials Using Optical Tactile Sensing |
| title_sort | embedded object detection and mapping in soft materials using optical tactile sensing |
| topic | Computer Science Applications Computer Networks and Communications Computer Graphics and Computer-Aided Design Computational Theory and Mathematics Artificial Intelligence General Computer Science |
| url | https://hdl.handle.net/1721.1/154045 |
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