Title :
Event-driven embodied system for feature extraction and object recognition in robotic applications
Author :
Wiesmann, G. ; Schraml, Stephan ; Litzenberger, Martin ; Belbachir, Ahmed Nabil ; Hofstatter, Michael ; Bartolozzi, Chiara
Author_Institution :
Safety & Security Dept., AIT Austrian Inst. of Technol., Vienna, Austria
Abstract :
A major challenge in robotic applications is the interaction with a dynamic environment and humans which is typically constrained by the capability of visual sensors and the computational cost of signal processing algorithms. Addressing this problem the paper presents an event-driven based embodied system for feature extraction and object recognition as a novel efficient sensory approach in robotic applications. The system is established for a mobile humanoid robot which provides the infrastructure for interfacing asynchronous vision sensors with the processing unit of the robot. By applying event-feature ”mapping” the address event representation of the sensors is enhanced by additional information that can be used for object recognition. The system is presented in the context of an exemplary application in which the robot has to detect and grasp a ball in an arbitrary state of motion.
Keywords :
feature extraction; humanoid robots; image sensors; mobile robots; object detection; object recognition; robot vision; asynchronous vision sensors; ball detection; ball grasping; dynamic environment-human interaction; event-driven embodied system; event-feature; feature extraction; mobile humanoid robot; object recognition; robotic applications; sensory approach; signal processing algorithm computational cost; visual sensors; Clustering algorithms; Feature extraction; Object recognition; Robot sensing systems; Voltage control;
Conference_Titel :
Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4673-1611-8
Electronic_ISBN :
2160-7508
DOI :
10.1109/CVPRW.2012.6238898