Unmanned Aerial Vehicle (UAV) and Search And Rescue (SAR) missions are hot topics of research these days. UAVs come in a wide range with different capabilities. Due to their applicability, they are being used for trivial as well as complex missions. The frequent mishaps and disasters have brought SAR into the limelight. SAR missions have unfavorable environments and short response times. SAR operations utilize various resources. Among them, UAV is one of the key resources, and it plays a vital role in such missions. This thesis explores the path planning of UAVs in SAR missions. Some of the area coverage algorithms have been considered and simulated in SITL with PX4 flight software stack in Gazebo. Quadcopter has been considered for the area coverage algorithms. Post-flight analysis of logs has been presented. Comparison between these algorithms has been deduced. Rapidly exploring Random Trees (RRT) has been considered as a target reaching algorithm in the SAR mission. RRT has been implemented in a 3D environment, modeling UAV as a 3D figure. Biased and unbiased flavors of Rapidly exploring Random Trees (RRT) have been implemented, and their comparison is discussed.