A rover is a planetary surface exploration device designed to move across the ground on a planet or a planetary-like body. Exploration rovers are increasingly becoming a vital part of the search for scientific evidence and discoveries on a planetary satellite of the Sun, such as the Moon or Mars. Reliable behavior and predictable locomotion of a rover is important. Understanding soil behavior and its interaction with rover wheels—the terramechanics—is of great importance in rover exploration performance. Up to now, many researchers have adopted Bekker’s semiempirical model to predict rover wheelsoil interaction, which is based on the assumption that soil is deformable when a pressure is applied to it. Despite this basic assumption of the model, the pressure-sinkage relation is not fully understood, and it continues to present challenges for rover designers. This article presents a new pressure-sinkage model based on dimensional analysis (DA) and results of bevameter tests. DA was applied to the test results in order to propose a new pressure-sinkage model by reducing physical quantitative parameters. As part of the work, a new bevameter was designed and built so that it could be successfully used to obtain a proper pressure-sinkage relation of Korean Lunar Soil Simulant (KLS-1). The new pressure-sinkage model was constructed by using three different sizes of flat plate diameters of the bevameter. The newly proposed model was compared successfully with other models for validation purposes.

In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.