# Unmanned Aerial Vehicle Landing on Rugged Terrain by On-Board LIDAR-Camera Positioning System
## 1 Introduction  
Unmanned aerial vehicles (UAVs) are highly mobile and lightweight devices that have garnered significant interest for outdoor missions, such as terrain surface rendering [1, 2], delivery of rescue materials [3], and inspection of large wild regions [4]. The terrains in these areas are rugged, and only some of the flat land is suitable for secure UAV landings. Therefore, to ensure successful landing without damage, the UAV should be able to land autonomously by detecting a suitable landing site after accomplishing its mission. In typical human-operated scenarios, autonomous landing capabilities can help the human operator determine whether the proposed location is suitable for landing. In autonomous decision scenarios, UAVs are more dependent on their autonomous landing capabilities, e.g., if the UAV requires an emergency landing because of low power or loss of connection with the ground station when it reaches an unknown location.  
Most UAV positioning or landing systems are based on positioning equipment, such as GPS or Inertial Navigation System (INS) devices [5, 6]. Despite wide use, GPS signals can be noisy, imprecise, and easily disrupted by obstacles in the field. Although INS systems can estimate five degrees of freedom, their accuracy can degrade over time due to error accumulation if there is no external correction. Additionally, INS systems that incorporate magnetometers are subject to local magnetic interference from buildings and other structures. These limitations make both GPS and INS systems unreliable for certain outdoor missions. Real-time kinematic (RTK) stations can significantly improve GPS accuracy and mitigate these problems; however, they can be ineffective if the GPS signal is lost or if there are interfering obstacles.  
Light detection and ranging (LIDAR) represents an increasingly popular type of vision system, which sends and receives laser beams to obtain 3D geometric information about the surroundings. Although LIDAR can be affected by direct sunlight, artificial light contamination, and adverse weather conditions, such as rain or fog, it remains relatively reliable under various lighting conditions. Therefore, LIDAR is widely applicable in 1. A LIDAR-camera system is developed to determine the position of a UAV and create geometric and color terrain maps of its environment, thereby solving the positioning problem in GPS-denied environments.
2. The proposed method based on LIDAR-camera mapping techniques can identify potential landing sites by fusing weighted energy cost functions of texture and geometric flatness, thereby ensuring terrain safety.
3. A dataset classified according to scene landing difficulty is established to facilitate UAV landing scene recognition. Additionally, an attention mechanism is added to the network to improve the accuracy and reliability of the scene analysis.  
The remainder of this report is organized as follows:  
* Section 2 discusses relevant previous work.
* Section 3 introduces the UAV positioning methods.
* Section 4 describes the UAV landing site selection system.
* Section 5 analyzes experimental results to evaluate the feasibility and robustness of the proposed method.  
Figure 1: Landing framework involving a LIDAR–camera positioning system.  
Section 6 presents the conclusions from this study and discusses future research directions.