# Overlap Avoidance of Mobility Models for Multi-UAVs Reconnaissance
## 2 Related Work & Research Motivation  
### Related Work  
Path planning-based reconnaissance establishes a path in advance by a central operator or planner before reconnoitering the scanning area. When the path is determined, a UAV flies along with the planned path [17]. In [18], the authors studied a path planning based on multiple UAVs for a polygonal-shaped area. The convex areas are partitioned into the same number as UAVs. The UAVs perform patrolling missions in their own assigned area. If a UAV malfunctions, the area allocated to each UAV is re-established. In [4; 5; 6; 8; 11], authors studied path-planning with optimization algorithms such as bee colony [4], ant colony [5], particle swarm [6; 8; 11], etc. They planed optimal paths to avoid threatening spots (e.g., an area easily detected by enemy radar) or to pass through important locations. On the other hand, if there are no important locations and threatening spots, the UAV moves straight to the destination established by the operator. In [19], the authors categorized the Paparazzi mobility model [20] and the Semi-Random Circular Movement model [21] into the path-planned method because those models move with certain patterns. The Paparazzi mobility model has five movement patterns which are stay-at, oval, way-point, eight, and scan. The probabilities for performing stay-at, oval, and scan are 30% each, while those of selecting eight and way-point patterns are 5% each. The Semi-Random Circular Movement model is proposed to patrol specific areas based on orbiting movement. In this model, a UAV generates several destinations to fly with a spiral pattern. Once arriving at the final destination, the UAV generates new destinations and repeats this process. The second approach is the reconnaissance based on the random mobility model which is well-known for modeling a movement of mobile node over a time period not only in mobile ad-hoc networks (MANET) but also in flying ad-hoc networks (FANET) [22]. The Random Waypoint model has been used as a basic model because of its simplicity [23]. A UAV generates a new destination randomly in the scanning area and then moves to that destination. When a UAV arrives at the destination, it repeats this process. The Random Markov Process model [12] is another random mobility model which stochastically decides one of three actions: Turn-left, straight ahead, and turn-right. The Gauss-Markov mobility model [24] represents realistic movement of a node because it determines the next coordinate from the previous velocity and direction. This model was designed to adjust randomness of diverse levels by applying one tuning parameter. The Enhanced Gauss-Markov mobility model [16] applies the Gauss-Markov model for UAV reconnaissance. This model considers smooth movement within the scanning area and a smooth turn in the boundary area. When a node approaches near the boundary area, it avoids a collision by changing mean direction deviation and mean variance of direction deviation. The Distributed Pheromone Repel (DPR) model [12] is inspired by the swarm intelligence which is the collective behavior of animals such as ants, bees, birds, etc. Ants interact by sharing their local information and move toward the strong pheromone. On the other hand, as the DPR model is designed for reconnaissance, UAVs move to areas with less pheromones. Each node has its own virtual map to store pheromone distribution and updates the map by broadcasting with nearby nodes. Other models based on pheromones are the Hybrid Markov Mobility Model with Pheromones (H3 MP) [13] and the Multiple Pheromone UAV Mobility Model (MPUMM) [14]. H3 MP is proposed for a patrol-surveillance scenario to detect targets in a realistic area that is non-square. It divides the area into \(N\) zones with the K-means algorithm. A UAV moves toward a zone with transition probabilities based on pheromones and the number of detections. In MPUMM, a UAV operates with two pheromones which are repulsive and attractive. The repulsive pheromone is used for reconnaissance.