Terrain Classification for Track-driven Agricultural Robots


Tan, Shing Chiang and Mahadhir, Khairul Azmi and Low, Cheng Yee and Dumitrescu, Roman and Tan Mohd Amin, Adam and Jaffar, Ahmed (2014) Terrain Classification for Track-driven Agricultural Robots. Procedia Technology, 15. pp. 776-783. ISSN 2212-0173

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A long-term goal of agricultural automation is to deploy intelligentrobots to facilitate labor-intensive tasks such as crop care or selective harvesting with minimum human supervision. To achieve this goal, the agricultural robots must be able to adapt themselves in response to various terrain conditions. The reason is that the terrain characteristics can jeopardize the performance of a robotin carrying out a taskor even causing it being trapped in the field. The aim of this work is to evaluate the effectiveness of using an intelligent algorithm, i.e. support vector machine (SVM) in recognizing various terrain conditions in an agricultural field. For this purpose, asmall tracked-driven mobile robot together witha terrain test bed has been developed. The terrain test bed emulates three types of terrain conditions, i.e. sand, gravel and vegetation. The tracked-driven robot is embedded with a low power MEMS accelerometer for measuring vibration signals resulted from the track-terrain interaction. An experimental study was conducted usinga SVMtrained with three different kernel functions, i.e. linear function, polynomial function and radial basis function (RBF). The results showed that the SVM can recognize different terrain conditions effectively. This work contributes to devising a self-adaptive agricultural robot in coping with changing terrain conditions.

Item Type: Article
Additional Information: 2nd International Conference on System-Integrated Intelligence: Challenges for Product and Production Engineering
Subjects: S Agriculture > S Agriculture (General)
T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 14 Oct 2014 04:30
Last Modified: 14 Oct 2014 04:31
URII: http://shdl.mmu.edu.my/id/eprint/5776


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