Title :
Modelling LGMD2 visual neuron system
Author :
Qinbing Fu;Shigang Yue
Author_Institution :
Computational Intelligence Lab (CIL), University of Lincoln, UK
Abstract :
Two Lobula Giant Movement Detectors (LGMDs) have been identified in the lobula region of the locust visual system: LGMD1 and LGMD2. LGMD1 had been successfully used in robot navigation to avoid impending collision. LGMD2 also responds to looming stimuli in depth, and shares most the same properties with LGMD1; however, LGMD2 has its specific collision selective responds when dealing with different visual stimulus. Therefore, in this paper, we propose a novel way to model LGMD2, in order to emulate its predicted bio-functions, moreover, to solve some defects of previous LGMD1 computational models. The mechanism of ON and OFF cells, as well as bio-inspired nonlinear functions, are introduced in our model, to achieve LGMD2´s collision selectivity. Our model has been tested by a miniature mobile robot in real time. The results suggested this model has an ideal performance in both software and hardware for collision recognition.
Keywords :
"Mobile robots","Collision avoidance","Mathematical model","Robot sensing systems","Biological system modeling","Firing"
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2015 IEEE 25th International Workshop on
DOI :
10.1109/MLSP.2015.7324313