DEVELOPMENT AND IMPLEMENTATION OF EMBEDDED SYSTEM ON GANESHBLUE UNDERWATER GLIDER
Autonomous Underwater Glider (AUG) requires integration of several systems in order perform maritime exploration mission. Deficiensies of a system can also affect performance of other systems. Performance of sensor data acquisition process will affect AUG ability to estimate its position, reachin...
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/53196 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Autonomous Underwater Glider (AUG) requires integration of several systems in
order perform maritime exploration mission. Deficiensies of a system can also
affect performance of other systems. Performance of sensor data acquisition
process will affect AUG ability to estimate its position, reaching destionation point,
and cause unsuitable AUG movements. Likewise, delays in the Finite State
Machine (FSM) will also cause delays in AUG state, event, or action.
This research aims to optimize embedded system in AUG GaneshBlue and develop
algorithms to make it able to to perform maritime exploration missions optimally.
Optimization is done by code refactoring on implemented navigation, guidance,
and control system. Optimization evaluation is based on software metrics in
Halstead metrics, cyclomatic complexity, and maintainability index of the source
code. Algorithm development for multi-coordinates maritime exploration mission
is carried out by integrating AUG, Ground Control Station (GCS), and a website.
AUG also has capability to perform failsafe action while on a mission.
Based on test results, optimization resulted in a reduction of average error for
NGC system interval on primary processors with mutlthread architecture reaching
89.73% and a reduction of average error for data acquisition interval on
secondary processors with Round Robin with Interrupt architecture reaching
99.69%. Based on software metrics, maintainability index is increased by up to
12%, reduction on Lines of Code (LOC) by 36%, and an increase in the quality of
implemented code based on Halstead metrics. |
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