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Haptic identification of objects using a modular soft robotic gripper
Abstract
This work presents a soft hand capable of robustly grasping and identifying objects based on internal state measurements. A highly compliant hand allows for intrinsic robustness to grasping uncertainty, but the specific configuration of the hand and object is not known, leaving undetermined if a grasp was successful in picking up the right object. A soft finger was adapted and combined to form a three finger gripper that can easily be attached to existing robots, for example, to the wrist of the Baxter robot. Resistive bend sensors were added within each finger to provide a configuration estimate sufficient for distinguishing between a set of objects. With one data point from each finger, the object grasped by the gripper can be identified. A clustering algorithm to find the correspondence for each grasped object is presented for both enveloping grasps and pinch grasps. This hand is a first step towards robust proprioceptive soft grasping.
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Cited by
Electronic skins and machine learning for intelligent soft robots
Shih, B., Shah, D., Li, J., Thuruthel, T. G., Park, Y.-L., Iida, F., Bao, Z., Kramer-Bottiglio, R., & Tolley, M. T. (2020) · Science Robotics · doi:10.1126/scirobotics.aaz9239 · Cited by 715
Soft robot perception using embedded soft sensors and recurrent neural networks
Thuruthel, T. G., Shih, B., Laschi, C., & Tolley, M. T. (2019) · Science Robotics · doi:10.1126/scirobotics.aav1488 · Cited by 678
3D printing for soft robotics – a review
Gul, J. Z., Sajid, M., Rehman, M. M., Siddiqui, G. U., Shah, I., Kim, K.-H., Lee, J.-W., & Choi, K. H. (2018) · Science and Technology of Advanced Materials · doi:10.1080/14686996.2018.1431862 · Cited by 428
Piazza, C., Grioli, G., Catalano, M. G., & Bicchi, A. (2019) · Annual Review of Control, Robotics, and Autonomous Systems · doi:10.1146/annurev-control-060117-105003 · Cited by 332
A Prestressed Soft Gripper: Design, Modeling, Fabrication, and Tests for Food Handling
Wang, Z., Torigoe, Y., & Hirai, S. (2017) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2017.2714141 · Cited by 295
Metadata
- Authors
- Homberg, B. S., Katzschmann, R. K., Dogar, M. R., & Rus, D.
- Venue
- 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Publisher
- IEEE
- Published
- 2015-09
- Pages
- 1698-1705
- OpenAlex
- W2205969003
- Cited by
- 282
- References
- 0
- FWCI
- 55.44
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Homberg, B. S., Katzschmann, R. K., Dogar, M. R., & Rus, D. (2015). Haptic identification of objects using a modular soft robotic gripper. 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). https://doi.org/10.1109/iros.2015.7353596
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