Collision detection in complex dynamic scenes using an LGMD-based visual neural network with feature enhancement.
IEEE Trans Neural Netw
; 17(3): 705-16, 2006 May.
Article
in En
| MEDLINE
| ID: mdl-16722174
The lobula giant movement detector (LGMD) is an identified neuron in the locust brain that responds most strongly to the images of an approaching object such as a predator. Its computational model can cope with unpredictable environments without using specific object recognition algorithms. In this paper, an LGMD-based neural network is proposed with a new feature enhancement mechanism to enhance the expanded edges of colliding objects via grouped excitation for collision detection with complex backgrounds. The isolated excitation caused by background detail will be filtered out by the new mechanism. Offline tests demonstrated the advantages of the presented LGMD-based neural network in complex backgrounds. Real time robotics experiments using the LGMD-based neural network as the only sensory system showed that the system worked reliably in a wide range of conditions; in particular, the robot was able to navigate in arenas with structured surrounds and complex backgrounds.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Algorithms
/
Pattern Recognition, Automated
/
Artificial Intelligence
/
Image Interpretation, Computer-Assisted
/
Image Enhancement
/
Information Storage and Retrieval
Type of study:
Diagnostic_studies
Language:
En
Journal:
IEEE Trans Neural Netw
Journal subject:
INFORMATICA MEDICA
Year:
2006
Document type:
Article
Country of publication:
United States