DocumentCode :
554862
Title :
Real-time reconstruction of orange tree model based on obstacle avoidance
Author :
Yongping Li ; Ping Cheng
Author_Institution :
Inf. & Eng. Coll., Ningbo Dahongying Univ., Ningbo, China
Volume :
8
fYear :
2011
fDate :
12-14 Aug. 2011
Firstpage :
4199
Lastpage :
4203
Abstract :
Based on obstacle avoidance of orange fruit harvesting robot, the real-time fruit tree model reconstruction is studied. Modular modeling method is adopted for the reconstruction, which extracts a standard module from the orange fruit tree by configuration study and then gets the fruit tree model after combining the module. Through the comparison between truncated cone module and cylinder module, step cylinder section is chose as the standard module. In order to supply the tree model in time, polygonal approximation is used in the standard module construction for the data reduction. The experiment for middle complexity tree model proved, that this method can realize real-time reconstruction of orange tree model, and the model is precise enough for obstacle avoidance.
Keywords :
agricultural products; approximation theory; collision avoidance; computational complexity; data reduction; image reconstruction; industrial robots; robot vision; shapes (structures); solid modelling; vegetation; data reduction; middle complexity tree model; modular modeling method; obstacle avoidance; orange fruit harvesting robot; polygonal approximation; real-time fruit tree model reconstruction; real-time orange tree model reconstruction; standard module extraction; step cylinder section; truncated cone module; Approximation methods; Collision avoidance; Data models; Real time systems; Robot kinematics; Three dimensional displays; modularization; polygonal approximation; real-time reconstruction; step cylinder section;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location :
Harbin, Heilongjiang
Print_ISBN :
978-1-61284-087-1
Type :
conf
DOI :
10.1109/EMEIT.2011.6023974
Filename :
6023974
Link To Document :
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