Tactile-based force estimation for interaction control with robot fingers
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866910866277924864 |
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| author | Chelly, Elie Cherubini, Andrea Fraisse, Philippe Amar, Faiz Ben Khoramshahi, Mahdi |
| author_facet | Chelly, Elie Cherubini, Andrea Fraisse, Philippe Amar, Faiz Ben Khoramshahi, Mahdi |
| contents | Fine dexterous manipulation requires reactive control based on rich sensing of manipulator-object interactions. Tactile sensing arrays provide rich contact information across the manipulator's surface. However their implementation faces two main challenges: accurate force estimation across complex surfaces like robotic hands, and integration of these estimates into reactive control loops. We present a data-efficient calibration method that enables rapid, full-array force estimation across varying geometries, providing online feedback that accounts for non-linearities and deformation effects. Our force estimation model serves as feedback in an online closed-loop control system for interaction force tracking. The accuracy of our estimates is independently validated against measurements from a calibrated force-torque sensor. Using the Allegro Hand equipped with Xela uSkin sensors, we demonstrate precise force application through an admittance control loop running at 100Hz, achieving up to 0.12+/-0.08 [N] error margin-results that show promising potential for dexterous manipulation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_13335 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Tactile-based force estimation for interaction control with robot fingers Chelly, Elie Cherubini, Andrea Fraisse, Philippe Amar, Faiz Ben Khoramshahi, Mahdi Robotics Fine dexterous manipulation requires reactive control based on rich sensing of manipulator-object interactions. Tactile sensing arrays provide rich contact information across the manipulator's surface. However their implementation faces two main challenges: accurate force estimation across complex surfaces like robotic hands, and integration of these estimates into reactive control loops. We present a data-efficient calibration method that enables rapid, full-array force estimation across varying geometries, providing online feedback that accounts for non-linearities and deformation effects. Our force estimation model serves as feedback in an online closed-loop control system for interaction force tracking. The accuracy of our estimates is independently validated against measurements from a calibrated force-torque sensor. Using the Allegro Hand equipped with Xela uSkin sensors, we demonstrate precise force application through an admittance control loop running at 100Hz, achieving up to 0.12+/-0.08 [N] error margin-results that show promising potential for dexterous manipulation. |
| title | Tactile-based force estimation for interaction control with robot fingers |
| topic | Robotics |
| url | https://arxiv.org/abs/2411.13335 |