Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots
Abstract Animals traverse vegetation by direct physical interaction using their entire body to push aside and slide along compliant obstacles. Current drones lack this interaction versatility that stems from synergies between body morphology and feedback control modulated by sensing. Taking inspirat...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-46967-5 |
| _version_ | 1827301071078293504 |
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| author | Emanuele Aucone Christian Geckeler Daniele Morra Lucia Pallottino Stefano Mintchev |
| author_facet | Emanuele Aucone Christian Geckeler Daniele Morra Lucia Pallottino Stefano Mintchev |
| author_sort | Emanuele Aucone |
| collection | DOAJ |
| description | Abstract Animals traverse vegetation by direct physical interaction using their entire body to push aside and slide along compliant obstacles. Current drones lack this interaction versatility that stems from synergies between body morphology and feedback control modulated by sensing. Taking inspiration from nature, we show that a task-oriented design allows a drone with a minimalistic controller to traverse obstacles with unknown elastic responses. A discoid sensorized shell allows to establish and sense contacts anywhere along the shell and facilitates sliding along obstacles. This simplifies the formalization of the control strategy, which does not require a model of the interaction with the environment, nor high-level switching conditions for alternating between pushing and sliding. We utilize an optimization-based controller that ensures safety constraints on the robot’s state and dampens the oscillations of the environment during interaction, even if the elastic response is unknown and variable. Experimental evaluation, using a hinged surface with three different stiffness values ranging from 18 to 155.5 N mm rad−1, validates the proposed embodied aerial physical interaction strategy. By also showcasing the traversal of isolated branches, this work makes an initial contribution toward enabling drone flight across cluttered vegetation, with potential applications in environmental monitoring, precision agriculture, and search and rescue. |
| first_indexed | 2024-04-24T16:16:51Z |
| format | Article |
| id | doaj.art-ac5caad9b4ae45968e790e3dc6a34a62 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-24T16:16:51Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-ac5caad9b4ae45968e790e3dc6a34a622024-03-31T11:26:22ZengNature PortfolioNature Communications2041-17232024-03-0115111110.1038/s41467-024-46967-5Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robotsEmanuele Aucone0Christian Geckeler1Daniele Morra2Lucia Pallottino3Stefano Mintchev4Environmental Robotics Laboratory, Department of Environmental Systems Science, ETH ZürichEnvironmental Robotics Laboratory, Department of Environmental Systems Science, ETH ZürichResearch Center “E. Piaggio”, Department of Information Engineering, University of PisaResearch Center “E. Piaggio”, Department of Information Engineering, University of PisaEnvironmental Robotics Laboratory, Department of Environmental Systems Science, ETH ZürichAbstract Animals traverse vegetation by direct physical interaction using their entire body to push aside and slide along compliant obstacles. Current drones lack this interaction versatility that stems from synergies between body morphology and feedback control modulated by sensing. Taking inspiration from nature, we show that a task-oriented design allows a drone with a minimalistic controller to traverse obstacles with unknown elastic responses. A discoid sensorized shell allows to establish and sense contacts anywhere along the shell and facilitates sliding along obstacles. This simplifies the formalization of the control strategy, which does not require a model of the interaction with the environment, nor high-level switching conditions for alternating between pushing and sliding. We utilize an optimization-based controller that ensures safety constraints on the robot’s state and dampens the oscillations of the environment during interaction, even if the elastic response is unknown and variable. Experimental evaluation, using a hinged surface with three different stiffness values ranging from 18 to 155.5 N mm rad−1, validates the proposed embodied aerial physical interaction strategy. By also showcasing the traversal of isolated branches, this work makes an initial contribution toward enabling drone flight across cluttered vegetation, with potential applications in environmental monitoring, precision agriculture, and search and rescue.https://doi.org/10.1038/s41467-024-46967-5 |
| spellingShingle | Emanuele Aucone Christian Geckeler Daniele Morra Lucia Pallottino Stefano Mintchev Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots Nature Communications |
| title | Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots |
| title_full | Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots |
| title_fullStr | Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots |
| title_full_unstemmed | Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots |
| title_short | Synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots |
| title_sort | synergistic morphology and feedback control for traversal of unknown compliant obstacles with aerial robots |
| url | https://doi.org/10.1038/s41467-024-46967-5 |
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