# Time Optimization of Unmanned Aerial Vehicles Using an Augmented Path
## 2 Literature Survey  
The delivery of products using a drone is not very popular in a country with huge diversity like India. We are working on an efficient algorithm to reduce the time efficiency of the drone so that the drone can deliver the product by saving time [1]. Research has investigated the optimization of modular drones so that they can form an efficient delivery system. Specifically, the battery life and motor have been investigated to save time and prevent delays in the delivery of products. The carrier placed in the drone should be strong enough has also been considered so that it can handle the weight of the parcel [2]. A study has also been performed considering the dense traffic. They developed the shortest path to deliver the product to the customer, and also stated that they have to install a recharging system in a different location to recharge the drone when needed so that there will be no delay due to a power deficiency [3]. Cost-efficient delivery of their product has also been explored by making an algorithm to solve the vehicle routing problem, which is to deliver to as many customers as possible in a particular set, which in turn saves the cost of drones, fuels, etc. [4]. The efficient delivery of parcels has also been researched by considering the vehicle routing problem, which is the major problem, but this is solved by using some mathematical equations and graphs so that it is easy to deliver in a particular set. They have thought of equipping drones in a particular vehicle and the vehicle stands in the middle of all the locations and the drones when all the parcels are delivered in a particular time, which saves a lot of time and it a cost-efficient idea [5]. Research has been preformed on battery-efficient drones' delivery, which makes the drones work more efficiently and can provide more working hours for the delivery of parcels. He decided to insert two batteries in the drone that are fully charged and if one of the batteries is discharged, then the other battery replaces the position of the battery, i.e., the two batteries are swapped, thus making it more efficient [6; 7; 8]. An algorithm has been developed for energy and range minimization, which will consequently help in cost-minimizing. This will also make their delivery very easy and efficient. They have considered a vehicle that runs in the delivery place and finds the shortest part for every nearby location by using some mathematical graphs and algorithms and from the location, the vehicle will launch a drone, which delivers to all the nearby places and returns to the vehicle before the battery is discharged. This idea will make delivery to all the nearby parcels very easy. All these studies mostly worked on the shortest path, most efficient battery, and fastest delivery, but no research has worked on efficient delivery based on the wind flow and environment to save time for the delivery [9; 10; 11; 12; 13]. The drone delivery is air transport, but in air transport, the basic constraint for the measurement of efficiency is flight time. All air transport is calculated in terms of flight time and so the basic idea and thus the tracking system is useless. As such, the shortest distance might not give the shortest time. This research paper is about this aspect [14; 15; 16; 17], mainly how to reduce time by using basic physics and algorithms to follow that path so that less time is used for reaching the destination and even considering the external interferences like wind speed, height, thrust, and even the weight of the carriage [18; 19; 20]. This paper proposes fuzzy control using two combinations of the algorithm: Virtual Reference Feedback Tuning (VRFT) and Active Disturbances Rejection Control (ADRC), to obtain the benefits of data-driven control and fuzzy control. This algorithm saves time in finding the optimal parameters of the controllers [21]. Working on the control problem for stochastic nonlinear systems, it is also based on fuzzy logic systems.