BUKU ABSTRAK - Universiti Putra Malaysia

Science, Technology & Engineering
Fresh Fruit Bunch (FFB) Hyperspectral Scanner
Assoc. Prof. Dr. Abdul Rashid Mohamed Shariff
Osama Mohamed Ben Saeed, Ahmad Rodzi Mahmud, Helmi Zulhaidi Mohd., Mohd. Din Amiruddin and
Meftah Salem Alfatni
Institute of Advanced Technology, University Putra Malaysia,
43400 UPM Serdang, Selangor, Malaysia.
+603-8946 7543; rashidpls3@gmail.com
This research deals with the determination of the ripeness of the oil palm fresh fruit bunch (FFB) using
the hyperspectral method. As the FFB have a convex surface, the conventional hyperspectral scanner is not
suitable to be used to determine the ripeness characteristics of the FFB. This research carried out modification
to make the conventional hyperspectral scanner suitable for maturity detection of FFB. This is achieved through
improvements to the illumination system of the hyperspectral scanner. The strategic positioning of the lamps
helps provide shadow free illumination. Data collected by this system is subjected to computer vision technique
for purposes of FFB classification. The resulting network is then integrated back into the system. Application
software developed in the Matlab 7.0 environment is used to classify the FFB. The classification mechanism
categorises the ripeness of oil palm fruit bunches into three different classes of oil palm fruit. The results are then
confirmed by a trained human grader. Our system helps to increase the quality of grading of fresh fruit bunches
(FFB). It will be useful to the oil palm industry, oil palm engineers, mill operators, plantation managers, small
holders and to the research community.
Keywords: Hyperspectral, grading system, maturity, illumination system, classification, oil palm, FFB
Development of Macro Language for Robotics Behaviour Representing Spatial
Relationships in Natural Language
Assoc. Prof. Dr. Abdul Rashid Mohamed Shariff
Md. Roshidul Hasan, Abdul Rahman Ramli and Ishak Iris
Institute of Advanced Technology, University Putra Malaysia,
43400 UPM Serdang, Selangor, Malaysia.
+603-8946 7543; rashidpls3@gmail.com
The deployment of robotics technologies in various fields has seen rapid growing during the last several
years in the world. In this context, cognition of behavioural robots to bring the benefits and potential of Artificial
Intelligence that has so far been lacking connectivity to the behaviour control in real world phenomena. Several
languages used earlier for different level of control structure of robots. These languages are very complex for most
users and need high skill to work. Real-world complexity combined with the complexity of robotic behaviours
and programming results in a situation that is difficult to understand. These complexities can be abridged by
developing macro languages with natural semantics and reserved words. This thesis aims to develop macro
language for robotics behaviour which could represent the spatial relationships. This will be done using natural
English level language as in describing tasks to another person. The macro languages will be developed based on
identified and verified 9-intersection model.
Keywords: Spatial relations, macro language, natural language, robot behaviours, semantic
190