| Summary: | Unmanned Aerial Vehicles, commonly known as drones,
have revolutionized various industries by providing efficient
solutions for area searches. They are widely used in fields
such as surveillance, disaster response, and agriculture. This
thesis explores optimizing drone search algorithms to reduce
search target times under obstacle avoidance circumstance.
Building on the Row Scan search algorithm, we investigate
the potential for a more rapid and versatile alternative. We
propose a random search algorithm to replace the traditional
Row Scan method. Through controlled variable simulations,
our findings indicate that the random search algorithm
significantly shortens the time required for UAVs to locate
targets, thereby improving search efficiency. This study
highlights the effectiveness of the random search algorithm in
optimizing UAV search operations, making it a promising
approach for future applications.
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