Vision-based grasp learning of an anthropomorphic hand-arm system in a synergy-based control framework
Author:
Affiliation:
1. Prisma Lab, University of Naples Federico II (DIETI), Naples, Italy.
2. Industry AMS, Naples, Italy.
3. ABB Corporate Research, Västerås, Sweden.
Abstract
Funder
FP7 Ideas: European Research Council
MUSHA National Italian project
Publisher
American Association for the Advancement of Science (AAAS)
Subject
Artificial Intelligence,Control and Optimization,Computer Science Applications,Mechanical Engineering
Reference36 articles.
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4. On the role of hand synergies in the optimal choice of grasping forces
5. An overview of 3D object grasp synthesis algorithms
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