## 1 Introduction  
Unmanned aerial vehicles (UAVs) in human-unreachable environments have aroused great interest in the civil, military, and engineering fields [1; 2; 3]. Within the group of drones, quadrotor helicopters have gained increasing interest, due to their maneuverability, simple structure, affordability, and agility. Information about the use of UAVs can be obtained from a number of new publications, with topics ranging from earthquake searching to the deployment of air-dropped goods for humanitarian purposes [4; 5; 6]. Furthermore, for missions such as delivering first-aid supplies, drones always need ground support, such as airports or landing stations. However, outside cities and bases, UAVs may quite easily encounter the situation that there is no suitable landing assistance infrastructure nearby [7; 8; 9]. This will severely limit the usability of drones. Flying animals, such as birds, can perch on trees, poles, and other non-flat surfaces which are not suitable for UAV landing. Equipped with this soft landing ability, birds may occupy a high vantage point [10]. They can stay there to search, forage, and rest for an extended period of time [11; 12]. As a high-challenge landing approach, perching refers to precise landing pose control and the effectiveness of energy absorption [13]. [PERSON] and [PERSON], of the MIT Computer Science and Artificial Intelligence Laboratory, have analyzed and presented fixed-wing precise drone landing tests and demonstrated that angles of attack are critical factors during the touchdown procedure [14]. [PERSON] from the Imperial College of London designed an aerial robot equipped with soft shock absorbers which can land on a convex surface with diameter longer than robot's body length [15]. Subsequently, many inspired mechanical devices have been investigated to test this hypothesis. For example, a pitch-up touchdown sequence, consisting of distance detection, UAV nose up, and soft contact with a landing zone, has been proposed by Stanford University [16; 17]. A passive micro-spine grapple was proposed for perching under tree branches [18]. UAVs are, at present, continue to be sent out to achieve safety, security, and rescue missions. Numerous robust control schemes have been developed to address the control problems in quadrotor helicopters associated with uncertainties and delays. In [19], a dynamic model of a quadrotor helicopter with a suspended payload was established, and a non-linear controller, without considering the parametric uncertainty, was also presented. In [20], a switching model predictive controller was proposed for the rejection of external disturbances. In [21], the author presented a feedback linearization control approach by considering the disturbance from the payload. To maintain the posture tracking performance against external uncertainties, an \(H_{\infty}\) theory-based approach was proposed in [22]. As an alternative method, the sliding model control technique was used in [23] to reduce the parameter variation effect on the closed-loop control system. In addition, a quadrotor transportation platform involves time-varying delays. In [24], constant state delays were analyzed within the quadrotor helicopter system. The input delays to the system were further discussed in [25]. In [26; 27; 28], radial basis function neural network (RBFNN)-based PID controllers were proposed to control quadrotor flying robots without separating the inner loop and the outer loop. However, the multiple non-linear uncertainties and disturbances were not considered in the design approach, which has a sub-optimal impact on the performance of UAVs. With the demand to land on a non-flat surface, this paper demonstrates the design and fabrication of a novel quadrotor helicopter system. The proposed platform uses a backstepping theory-based flight controller working with a neural network algorithm, which enables a drone to safely land on a non-flat platform. In this paper, a non-linear flight controller is proposed.