Abstract
The nature of continuum soft robots calls for novel perception solutions, which can provide information on the robot's shape while not substantially modifying their bodies' softness. One way to achieve this goal is to develop innovative and completely deformable sensors. However, these solutions tend to be less reliable than classic sensors for rigid robots. As an alternative, we consider here the use of monocular cameras. By admitting a small rigid component in our design, we can leverage well-established solutions from mobile robotics. We propose a shape sensing strategy that combines a SLAM algorithm with nonlinear optimization based on the robot's kinematic model. We prove the method's effectiveness in simulation and with experiments of a single-segment continuous soft robot with a camera mounted to the tip. We achieve mean relative translational errors below 9% simulations and experiments alike, and as low as 0.5% on average for some simulation conditions.
Original language | English |
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Title of host publication | Proceedings of the 5th International Conference on Soft Robotics (RoboSoft 2022) |
Publisher | IEEE |
Pages | 795-801 |
ISBN (Print) | 978-1-6654-0828-8 |
DOIs | |
Publication status | Published - 2022 |
Event | 5th International Conference on Soft Robotics, RoboSoft 2022 - Edinburgh, United Kingdom Duration: 4 Apr 2022 → 8 Apr 2022 |
Conference
Conference | 5th International Conference on Soft Robotics, RoboSoft 2022 |
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Country/Territory | United Kingdom |
City | Edinburgh |
Period | 4/04/22 → 8/04/22 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Simultaneous localization and mapping
- Shape
- Robot kinematics
- Robot vision systems
- Estimation
- Kinematics
- Soft robotics