## 2 Literature Review
[17] investigated previous studies of the use of UAVs in wildfires and suggested cooperative autonomous systems for wildland firefighting using both UAVs and UGVs. In this case, UGVs are used to transport small UAVs to fire areas and as refueling stations. [PERSON] et al. [18] proposed the system to collect data autonomously using UAVs and UGVs together at a construction site. Since the UGVs have a problem in that it is difficult to move in places with many obstacles, in this case, the UAVs can be used to scan the point of interest. They tested the proposed system in an indoor environment with obstacles like reality and evaluated the performance. [PERSON] et al. [19] developed an efficient route planning to build ground maps using UAVs and UGVs cooperatively. They collected the ground information and then suggested route planning algorithms to minimize the total travel distance of vehicles. [PERSON] et al. [20] designed surveillance system using UAVs, UGVs and UMVs simultaneously to find someone trying to escape from a restricted area early. The proposed model was verified through a case study, and as a result, it showed better performance in terms of early detection and detection area compared to the existing model. Several studies have been conducted to design the optimal route when UAVs, vehicles, or UGVs is simultaneously put into the delivery business. [PERSON] et al. [21] established the optimal routing plan when using drones in the existing vehicle-only delivery system with minimizing total CO\({}_{2}\) emissions as well as delivery costs of both vehicles and UAVs. They used genetic algorithms to solve the presented problems and experimental results showed that using UAVs for delivery is more effective in terms of both cost saving and CO\({}_{2}\) emission reduction. [PERSON] et al. [22] dealt with the instant delivery by combining vehicles and UAVs. It is assumed that a vehicle carrying a multiple UAVs operates at multiple stop points, and the UAV performs a single delivery at each stop point. They decided the location and the number of vehicles stops, and delivery routing of each vehicle and UAV with minimizing the number of vehicles put into delivery and total travel time. [PERSON] et al. [23] is similar to [22], except that the UAV covers multiple deliveries. In addition, they considered the change in energy consumption according to the payload of the UAV and developed hybrid heuristic algorithm with minimizing total service time including delivery and operation time. [PERSON] et al. [24] dealt with vehicle-UAV routing problem of delivery services considering traffic restrictions. When a vehicle equipped with a UAV starts from a warehouse and operates a delivery route, it is assumed that a UAV is used for delivery to a place where the vehicle cannot enter due to traffic restrictions such as vehicle-type restriction and half-side traffic. They found the optimal routing plan for each vehicle and UAV with minimizing total cost and energy consumption. Genetic algorithm was used to solve the presented problem and proposed model was evaluated through experimental analysis. [PERSON] and [PERSON] [25] established an optimal operation plan that can minimize the service time so that the delivery means returns to the point of departure as quickly as possible when parcels are delivered by trucks and UAVs. In previous studies, it was common for UAVs to depart from ground vehicles after being loaded onto them. However, their study differs in that it also deals with cases where parcels are delivered by UAVs directly from the distribution center to customers. [PERSON] et al. [26] considered a scenario in which UAVs and UGVs collaborate to explore the planetary surface. In general, UAVs have an energy constraint, but they have the advantage of being able to reach the target points that UGVs cannot. Based on these general characteristics of UGVs and UAVS, they proposed a UGV-UAV hybrid system that utilizes UGVs as a moving charging station for UAVs and UAVs as a means to reach a target point.