We are developing soft skin for robots with sensitivity exceeding that of human skin. It gives information about shape, texture, normal force and shear force.  The soft sensitive fingers will give robots advantages in many aspects of manipulation, whether on the factory floor or in the home. The fingers can tell the robot about the 3D pose of a grasped object, and whether the object is hard, soft, smooth, or rough. In this project we are building improved touch sensing hardware, and are developing algorithms to exploit the rich information being provided.

This is a continuation of the same project "Exploring the World of High Definition Touch" by Ted Adelson and John Leonard.

Publications:

1. C. Wang, S. Wang, B. Romero, F. Veiga, and E. Adelson, “SwingBot: Learning Physical Features from In-hand Tactile Exploration for Dynamic Swing-up Manipulation,” in IROS 2020 (accepted).
2. S. Dong, S. Wang, Y. She, N. Sunil, A. Rodriguez, and E. Adelson, “Cable Manipulation with a Tactile-Reactive Gripper,” in Robotics: Science and Systems XVI, 2020, doi: 10.15607/RSS.2020.XVI.029 [Online]. Available: https://doi.org/10.15607/RSS.2020.XVI.029
3. B. Romero, F. Veiga, and E. Adelson, “Soft, Round, High Resolution Tactile Fingertip Sensors for Dexterous Robotic Manipulation,” in 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 4796–4802, doi: 10.1109/ICRA40945.2020.9196909 [Online]. Available: https://doi.org/10.1109/ICRA40945.2020.9196909
4. S. Wang, J. Wu, X. Sun, W. Yuan, W. T. Freeman, J. B. Tenenbaum, and E. H. Adelson, “3D Shape Perception from Monocular Vision, Touch, and Shape Priors,” in IROS 2018, 2018 [Online]. Available: https://doi.org/10.1109/IROS.2018.8593430
5. 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
6. R. Calandra, A. Owens, D. Jayaraman, J. Lin, W. Yuan, J. Malik, E. H. Adelson, and S. Levine, “More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch,” IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3300–3307, Oct. 2018 [Online]. Available: https://doi.org/10.1109/LRA.2018.2852779
7. W. Yuan, Y. Mo, S. Wang, and E. H. Adelson, “Active Clothing Material Perception using Tactile Sensing and Deep Learning,” in ICRA 2018, 2018 [Online]. Available: https://doi.org/10.1109/ICRA.2018.8461164
8. S. Dong, W. Yuan, and E. Adelson, “Improved GelSight Tactile Sensor for Measuring Geometry and Slip,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, 2017 [Online]. Available: http://doi.org/10.1109/IROS.2017.8202149
9. J. Li, S. Dong, and E. Adelson, “Slip Detection with Combined Tactile and Visual Information,” in ICRA 2018, 2018 [Online]. Available: https://doi.org/10.1109/ICRA.2018.8460495
10. W. Yuan, S. Dong, and E. H. Adelson, “GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force,” Sensors, vol. 17, no. 12, Nov. 2017 [Online]. Available: https://doi.org/10.3390/s17122762
11. G. Izatt, G. Mirano, E. Adelson, and R. Tedrake, “Tracking objects with point clouds from vision and touch,” in Robotics and Automation (ICRA), 2017 IEEE International Conference on, 2017, pp. 4000–4007 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989460
12. W. Yuan, S. Wang, S. Dong, and E. Adelson, “Connecting Look and Feel: Associating the visual and tactile properties of physical materials,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, 2017 [Online]. Available: https://doi.org/10.1109/CVPR.2017.478
13. W. Yuan, C. Zhu, A. Owens, M. A. Srinivasan, and E. H. Adelson, “Shape-independent Hardness Estimation Using Deep Learning and a GelSight Tactile Sensor,” in 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore, 2017 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989116