DocumentCode :
3284354
Title :
An intelligent vision system for object localization and obstacle avoidance for an indoor service robot
Author :
Hema, C.R. ; Paulraj, M.P. ; Adom, Abdul Hamid Bin ; Sim, K.F. ; Palaniappan, Rajkumar
Author_Institution :
Fac. of Eng., Karpagam Univ., Coimbatore, India
fYear :
2011
fDate :
19-20 Dec. 2011
Firstpage :
117
Lastpage :
122
Abstract :
Housekeeping robots are service robots specially designed to perform housekeeping tasks such as cleaning and vacuuming. In this research an intelligent vision system for object localization and obstacle avoidance for an indoor service robot was developed. The vision system aids in identifying objects and obstacles in a controlled environment. The system comprises of a digital camera which is placed on the front panel of the robot. Captured images are processed to segment object of the image. A simple neural network model was developed to identify obstacles and objects. Visual servoing is used to locate the object that fall out of the gripper range and visual range as well. The developed vision system has successfully tested on the house keeping robot for real time navigation and pick & place operation.
Keywords :
collision avoidance; grippers; image segmentation; neural nets; object detection; robot vision; service robots; video cameras; visual servoing; digital camera; gripper; housekeeping robots; image segmentation; indoor service robot; intelligent vision system; neural network model; object identification; object localization; obstacle avoidance; pick & place operation; real time navigation; visual servoing; Cameras; Computer crashes; Educational institutions; Image segmentation; Robot vision systems; Visualization; Object & obstacle identification; neural network; real time navigation; visual servoing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research and Development (SCOReD), 2011 IEEE Student Conference on
Conference_Location :
Cyberjaya
Print_ISBN :
978-1-4673-0099-5
Type :
conf
DOI :
10.1109/SCOReD.2011.6148719
Filename :
6148719
Link To Document :
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