A self-learning framework for statistical ground classification using radar and monocular vision

Journal of Field Robotics

Volumn 32, Issue 1, 2015, Pages 20-41

  Milella, Annalisa ^a   Reina, Giulio ^b   Underwood, James ^c  

^a INSTITUTE OF INTELLIGENT SYSTEMS FOR AUTOMATION   (Italy)

^b UNIVERSITY OF SALENTO   (Italy)

^c UNIVERSITY OF SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

LANDFORMS; NAVIGATION SYSTEMS; ROBOTS; SOCIAL NETWORKING (ONLINE); VISION;

CLASSIFICATION ACCURACY; ENVIRONMENTAL CONDITIONS; MAHALANOBIS DISTANCES; ONLINE LEARNING STRATEGY; STATISTICAL FEATURES; TERRAIN CHARACTERISTICS; UNMANNED GROUND VEHICLES; VISUAL CLASSIFICATION;

RADAR;

EID: 84916639252     PISSN: 15564959     EISSN: 15564967     Source Type: Journal    
DOI: 10.1002/rob.21512     Document Type: Article

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