Liquids Identification and Manipulation via Digitally Fabricated Impedance Sensors
Author:
Affiliation:
1. Massachusetts Institute of Technology,Computer Science and Artificial Intelligence Laboratory (CSAIL),Cambridge,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10609961/10609862/10610518.pdf?arnumber=10610518
Reference39 articles.
1. Toward next-generation learned robot manipulation
2. Learning human–environment interactions using conformal tactile textiles
3. Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching
4. Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning
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