Large-scale supervised learning of the grasp robustness of surface patch pairs

2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2016

Volumn , Issue , 2017, Pages 216-223

  Seita, Daniel ^a   Pokorny, Florian T ^a,b   Mahler, Jeffrey ^a   Kragic, Danica ^b   Franklin, Michael ^a   Canny, John ^a   Goldberg, Ken ^a  

^a DEPARTMENT OF INDUSTRIAL ENGINEERING AND OPERATIONS RESEARCH   (United States)

^b ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; DEEP LEARNING; LEARNING SYSTEMS; ROBOT PROGRAMMING; ROBOTS; SUPERVISED LEARNING;

COMPUTATIONALLY EFFICIENT; DISJOINT SUBSETS; LOCAL SURFACES; MEAN ABSOLUTE ERROR; MONTE CARLO SAMPLING; RANDOM FORESTS; SUPERVISED LEARNING METHODS; SURFACE PATCHES;

MONTE CARLO METHODS;

EID: 85015928918     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIMPAR.2016.7862399     Document Type: Conference Paper

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