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Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2016-June, Issue , 2016, Pages 2167-2174

Optimizing for what matters: The top grasp hypothesis

(3) Kappler, Daniel a Schaal, Stefan a,b Bohg, Jeannette a

a MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS (Germany)

b UNIVERSITY OF SOUTHERN CALIFORNIA (United States)

Author keywords

[No Author keywords available]

Indexed keywords

OPTIMIZATION; STOCHASTIC SYSTEMS;

BINARY LABELS; LARGE MARGINS; NOISY SENSORS; POINT CLOUD; QUANTITATIVE EXPERIMENTS; ROBOTIC GRASPING; STOCHASTIC GRADIENT DESCENT; SUPERVISED LEARNING METHODS;

ROBOTICS;

EID: 84977512308 PISSN: 10504729 EISSN: None Source Type: Conference Proceeding
DOI: 10.1109/ICRA.2016.7487367 Document Type: Conference Paper

Times cited : (4)

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