THESIS
2017
Abstract
Searching operation is one of the most common applications of robotics. Ability to operate
continuously greatly influences the applicability of autonomous robots in searching operation.
This work proposes a design of swarm robotic system for long-term searching operations.
Detailed specifications and the macroscopic behavior model are shown. A novel mechanism of
adjusting task-charge ratio automatically is proposed. A searching algorithm based on the
Particle Swarm Optimization is implemented in the simulation environment. Several sets of
simulation experiments were then conducted. The experimental results justify the survivability
and scalability of the proposed system. In every experiment, system energy level keeps
relatively stable throughout the whole simulation. A modified...[
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Searching operation is one of the most common applications of robotics. Ability to operate
continuously greatly influences the applicability of autonomous robots in searching operation.
This work proposes a design of swarm robotic system for long-term searching operations.
Detailed specifications and the macroscopic behavior model are shown. A novel mechanism of
adjusting task-charge ratio automatically is proposed. A searching algorithm based on the
Particle Swarm Optimization is implemented in the simulation environment. Several sets of
simulation experiments were then conducted. The experimental results justify the survivability
and scalability of the proposed system. In every experiment, system energy level keeps
relatively stable throughout the whole simulation. A modified version of Response Threshold
Model is proposed for this system to adjust the task-charge ratio according to the environmental
conditions adaptively. The simulation results show that the searching performance is better than
the one using manually tuned parameters.
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