Learning visual object categories for robot affordance prediction

International Journal of Robotics Research

Volumn 29, Issue 2-3, 2010, Pages 174-197

  Sun, Jie ^a   Moore, Joshua L ^a   Bobick, Aaron ^a   Rehg, James M ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AFFORDANCES; AUTONOMOUS ROBOT; CA MODEL; DATA SETS; DEPTH INFORMATION; DIRECT MAPPING; IMAGE FEATURES; INDOOR MOBILE ROBOTS; INTERMEDIATE REPRESENTATIONS; LEARNING AND TRAINING; LEARNING PROBLEM; NEW MODEL; PROBABILISTIC GRAPHICAL MODELS; SENSOR MEASUREMENTS; TRAVERSABILITY; VISUAL OBJECTS;

FORECASTING; GRAPHIC METHODS; NAVIGATION;

ROBOTS;

EID: 77949346006     PISSN: 02783649     EISSN: 17413176     Source Type: Journal    
DOI: 10.1177/0278364909356602     Document Type: Article

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