The goal of this project is to develop the technologies for a robot manipulator to perform autonomous object exploration of previously unseen objects and to iteratively adapt/refine/verify its own perception and manipulation skills. In particular, we want to demonstrate that the following are possible and practical:
- Unsupervised and safe exploration of a novel object.
- Automatic data collection, experiment labeling, and feature/parameter extraction.
- Iterative improvement and verification of manipulation skills for novel objects.
We want to study the processes of on-line data collection and skill testing. In some cases, a robot will have good priors from similar objects previously explored, and will need to verify them. In other cases, a robot will have to gather new data and update its manipulation behaviors.
[January-1-2018 to current]
S. Dong, D. Ma, E. Donlon, and A. Rodriguez, “Maintaining Grasps within Slipping Bounds by Monitoring Incipient Slip,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 3818–3824 [Online]. Available: https://doi.org/10.1109/ICRA.2019.8793538. [Accessed: 09-Sep-2019]
M. Bauza, O. Canal, and A. Rodriguez, “Tactile Mapping and Localization from High-Resolution Tactile Imprints,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 3811–3817 [Online]. Available: https://doi.org/10.1109/ICRA.2019.8794298. [Accessed: 09-Sep-2019]
E. Donlon, S. Dong, M. Liu, J. Li, E. Adelson, and A. Rodriguez, “GelSlim: A High-Resolution, Compact, Robust, and Calibrated Tactile-sensing Finger,” in IROS 2018, 2018 [Online]. Available: https://doi.org/10.1109/IROS.2018.8593661
Siyuan Dong and Alberto Rodriguez, "Tactile-Based Insertion for Dense Box-Packing", IROS 2019.