Chen, Z;
Crucianelli, L;
Versace, E;
Jamone, L;
(2025)
Exploring Tactile Perception for Object Localization in Granular Media: A Human and Robotic Study.
In:
2025 IEEE International Conference on Development and Learning ICDL 2025.
IEEE: Prague, Czech Republic.
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Abstract
Localizing buried objects in granular media, such as sand, poses a significant challenge in robotics, with limited insight into human tactile capabilities in these environments. This study presents a novel approach to tactile-based localization through: (1) a human study with 12 participants assessing fingertip sensitivity to tactile cues from buried objects, and (2) a robotic experiment using a tactile-equipped robotic arm and a Long Short-Term Memory (LSTM) model to detect object presence. Drawing from granular media particle interaction theory, we hypothesize tactile cues extend up to 7 cm. Human results confirm detection with 70.7% precision at a 6.9 cm distance (median 2.7 cm). Robotic results align, with the LSTM model detecting objects at 7.1 cm, though with a better median (6 cm) but lower precision (40%). This work enhances understanding of human tactile perception in granular media and introduces a robotic system to study human exploration strategies and enable autonomous applications in archaeology, space exploration, and search and rescue.
| Type: | Proceedings paper |
|---|---|
| Title: | Exploring Tactile Perception for Object Localization in Granular Media: A Human and Robotic Study |
| Event: | 2025 IEEE International Conference on Development and Learning (ICDL) |
| Dates: | 16 Sep 2025 - 19 Sep 2025 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ICDL63968.2025.11204359 |
| Publisher version: | https://doi.org/10.1109/icdl63968.2025.11204359 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Location awareness, Archeology, Sensitivity, Media, Robot sensing systems, Manipulators, Space exploration, Robots, Long short term memory, Buried object detection |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10218530 |
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