**1. Introduction**

Multicopter rotorcraft unmanned aerial vehicles (UAVs) are less susceptible to turbulence as compared with similar-sized fixed wing aircraft. Among the rotorcraft, the quadcopter is the most commonly used UAV, because of its mechanical simplicity and performance [1–3]. Of late, the applications of quadcopter UAVs, i.e., drones are increasing dramatically due to less risk and more benefits to the operators and users in the Earth's atmosphere. A literature review revealed that the application of drones with improved payload capability for high-endurance planetary exploration has been emerging in aerospace industries worldwide owing to the fact that a drone can map a larger planet area than a rover at a resolution far better than the existing satellites or orbiters [4,5]. It is well known that airborne platforms cover much larger distances in a single mission than a rover and can transmit high-resolution images of very rocky or steep terrain better than state-of-the-art orbiting spacecraft. Orbiters extend the facility to map large areas for a longer period of time with restricted resolution. Landers can handle the planet's surface and atmospheric sampling but are limited to the close vicinity of the landing site. The mobility of the airborne platform is a major concern. To overcome these restrictions of orbiters and landers, we have proposed MR simulation of a high-endurance quadcopter UAV with dual-head electromagnetic propulsion (EMP) devices to maneuver to interesting sites lucratively for a longer duration through the prescribed trajectory.

A literature review revealed that there are eight listed planets and more than 160 moons known to us in the solar system. Among the planets, it has been reported that Venus, Earth, Mars, Jupiter, Saturn, Uranus, and Neptune have noteworthy atmospheres. The largest moon of Saturn, namely Titan, has been identified to have a dense atmosphere for facilitating the mobility of the airborne platforms. Over the decades, Mars has been one of the fascinating planets for scientific exploration. Flying a drone in the environment of Mars presents a major challenge, mainly because of the atmospheric characteristics of Mars. It has been reported that the density of the atmosphere of Mars is extremely low in the order of 1/70 as compared with that on Earth's surface [6], which demands the high-speed rotor to generate sufficient lift at a low Reynolds number. The speed of sound on Mars is approximately 20% less as compared with that on Earth [6], which creates the high Mach number flows. At this atmospheric condition, designing an airborne platform for planet exploration is a challenging task. In this paper, we proposed a viable option of a new generation quadcopter UAV integrated with lightweight feedback-controlled dual-head EMP devices which achieves the variable-speed spinning rotors to obtain a desirable lift with an efficient guidance, navigation, and control system, in accordance with local atmospheric properties, for high-endurance Earth and other planetary explorations with the aid of MR simulation to meet the flight path demands of the mission.

Although many studies have been carried out on the design and development of multicopter rotorcraft from a different perspective, a limited number of studies have been carried out on MR simulation based on a quadcopter UAV and an X-Plane flight simulator [7–9]. In quadcopters, two motors rotate in a clockwise (CW) direction, and the remaining two motors rotate in a counterclockwise (CCW) direction, which produce zero angular momentum. In order to control the yaw, where the copter turns left and right, either the CW or CCW propellers are required to speed up or slow down to cause angular momentum to turn the copter. Quadcopters are currently used in agricultural, scientific, and commercial fields, including the military. The quadcopter works according to the speed of each rotor. Flight controller hardware is the head of any UAV, including the quadcopter. Today, the Pixhawk controller is widely used for UAV applications due to its low cost and better performance [7–9] and it comes with autopilot open source software and firmware.

The necessity for UAV simulations is increasing largely because there is a great deal of research taking place on UAV exploration [9–11]. A literature review revealed that many undesirable accidents have occurred during UAV operations due to the lack of professional pilot training [12–14]. Therefore, it is necessary, rather desirable, and perhaps inevitable, to develop a training device, such as the UAV simulator for new UAV users, and also for further research and development. UAV simulations have shown many benefits, including better understanding of a system and experimental flight tests before a real UAV fight. In the industry, a considerable number of flight simulation softwares are available, including X-Plane [15–17], FlightGear [18], Gazebo [9], and MAV3DSim [19]. The three main types of existing simulations are virtual reality (VR) simulation [20], augmented reality (AR) simulation [21], and mixed reality (MR) simulation [22]. The virtual reality simulation is a fully immersive type of simulation; it is used in computer technology to create a simulated environment. The augmented reality simulation is overlaid digital information in the real world. The mixed reality simulation is a combination of the virtual part, together with the real part, and it interacts in real time. Various research methods have been conducted on these three simulations, including the UAV field. Gongjin Lan et al. (2016) [23] developed UAV-based virtual reality systems and Shubo Wang et al. (2017) [24] constructed a virtual reality platform for UAV deep learning. Yuan Wang et al. and Li Yi-bo et al. introduced UAV with augmented reality technologies [25,26]. In MR simulation, Martin Selecký et al. [27] proposed a design for a communication architecture in unmanned systems. Fernando López Peña et al. (2017) [28] discussed an initial phase of the MR simulator for autonomous UAVs. Saimouli Katragadda et al. (2019) [29] developed a stereoscopic MR for UAV search and rescue.

Nowadays, UAVs are used for long-time missions for strategic defense, agricultural, surveillance, and rescue operations during a natural calamity. Additional surveillance applications include pipeline security, livestock monitoring, wildfire mapping, home security, road patrol, transportation, photography, and other entertainments. The main limitation of the long-time missions is the limited flight endurance due to the visibility problem of the UAV. It is well known that most UAVs have a live camera tracking system and global positioning system (GPS), but a user cannot see the overall view of an UAV during the use of these systems.

Although a large volume of simulation studies on UAVs are available in the open literature, there are no studies that address the overall view and performance of MR simulation of UAVs [27–29], which we have addressed, herein, along with the preliminary design of a quadcopter UAV governed by dual-head EMP devices for high endurance planetary explorations. More specifically, in this paper, we introduce a new MR simulation based on a quadcopter UAV and an X-Plane flight simulator (version 10.51). Herein, we present an overall view of the real-time performance of an UAV, which enables us to see the live performance of a real UAV quadcopter on a simulation platform. Using this MR simulation technique, we can solve the problem of limited flight endurance due to visibility problems during a long-time mission of any quadcopter.
