Search Results (60)

This article addresses the scanning path plan strategy of a rover team composed of three rovers, such that the team explores unknown dark outer space environments. This research considers a dark outer space, where a rover needs to turn on its light and camera simultaneously to measure a limited space in front of the rover. The rover team is deployed from a symmetric base station, and the rover team’s mission is to scan a bounded obstacle-rich workspace, such that there exists no remaining detection hole. In the team, only one rover, the hauler, can locate itself utilizing stereo cameras and Inertial Measurement Unit (IMU). Every other rover follows the hauler, while not locating itself. Since Global Navigation Satellite System (GNSS) is not available in outer space, the localization error of the hauler increases as time goes on. For rover’s location estimate fix, one occasionally makes the rover home to the base station, whose shape and global position are known in advance. Once a rover is near the station, it uses its Lidar to measure the relative position of the base station. In this way, the rover fixes its localization error whenever it homes to the base station. In this research, one makes the rover team fully scan a bounded obstacle-rich workspace without detection holes, such that a rover’s localization error is bounded by letting the rover home to the base station occasionally. To the best of our knowledge, this article is novel in addressing the scanning path plan strategy, so that a rover team fully scans a bounded obstacle-rich workspace without detection holes, while fixing the accumulated localization error occasionally. The efficacy of the proposed scanning and localization strategy is demonstrated utilizing MATLAB-based simulations. Full article

The space environment is characterized by unstructured features, sparsity, and poor lighting conditions. The difficulty in extracting features from the visual frontend of traditional SLAM methods results in poor localization and time-consuming issues. This paper proposes a rapid and real-time localization and mapping method for star chart surveyors in unstructured space environments. Improved localization is achieved using multiple sensor fusion to sense the space environment. We replaced the traditional feature extraction module with an enhanced SuperPoint feature extraction network to tackle the challenge of challenging feature extraction in unstructured space environments. By dynamically adjusting detection thresholds, we achieved uniform detection and description of image keypoints, ultimately resulting in robust and accurate feature association information. Furthermore, we minimized redundant information to achieve precise positioning with high efficiency and low power consumption. We established a star surface rover simulation system and created simulated environments resembling Mars and the lunar surface. Compared to the LVI-SAM system, our method achieved a 20% improvement in localization accuracy for lunar scenarios. In Mars scenarios, our method achieved a positioning accuracy of 0.716 m and reduced runtime by 18.682 s for the same tasks. Our approach exhibits higher localization accuracy and lower power consumption in unstructured space environments. Full article

This article explores the influence of lunar regolith and rover structure, such as mast design and material composition, on antenna parameters. It focuses on the distinctive difficulties of communication in the lunar environment, which need specialized antenna solutions. This study specifically examines the performance of antennas on the lunar Rashid rover within the Atlas crater, a landing site on the moon, considering two antenna types: a sleeve dipole antenna and an all-metal patch antenna. Thermal analyses reveal temperatures in the Atlas crater can exceed 80 °C during lunar mid-day. The findings highlight the effect of different materials used as thermal coatings for Rashid rover antennas, as well as the influence of rover materials on antenna performance. Furthermore, this study extends to analyze the conductivity and depth of lunar regolith within the Atlas crater. Given the critical role of antennas in wireless communication, understanding how lunar regolith properties affect antenna performance is essential. This research contributes to the creation of a strong communication system for the Rashid rover and future lunar missions by considering the features of the lunar regolith in addition to the rover’s size and material attributes. Full article

A detailed analysis of the panoramic camera data from the 27th to 33rd lunar days was conducted on the high-resolution scenes captured by the Yutu-2 rover stations. This analysis aimed to determine the detailed morphological parameters of the 2015 impact craters within the inspection area. The levels of degradation observed in the impact craters were determined alongside the surface features. Subsequently, the degradation patterns of the impact craters located within the Yutu-2’s roving area and the distribution patterns of the morphological parameters were analysed and investigated. The results of the analysis indicate that 94% of the impact craters exhibited severe degradation, 80% had depth-to-diameter ratios (DDRs) ranging from 0.07 to 0.17, and the remaining craters were moderately degraded. The DDRs of the impact craters exhibited a declining trend with an increase in the dimensions of the impact craters. Additionally, the degree of degradation of impact crater populations demonstrated a decreasing trend. In general, the impact craters along the rover’s route exhibited severe degradation, with the population of degradation degrees gradually decreasing with increasing diameter. Full article

High-resolution and high-accuracy mapping products of the Lunar South Pole (LSP) will play a vital role in future lunar exploration missions. Existing lunar global mapping products cannot meet the needs of engineering tasks, such as landing site selection and rover trajectory planning, at the LSP. The Lunar Reconnaissance Orbiter (LRO)’s narrow-angle camera (NAC) can acquire submeter images and has returned a large amount of data covering the LSP. In this study, we combine stereo-photogrammetry and photoclinometry to generate high-resolution digital orthophoto maps (DOMs) and digital elevation models (DEMs) using LRO NAC images for a candidate landing site at the LSP. The special illumination and landscape characteristics of the LSP make the derivation of high-accuracy mapping products from orbiter images extremely difficult. We proposed an easy-to-implement shadow recognition and contrast stretching method based on the histograms of the LRO NAC images, which is beneficial for photogrammetric and photoclinometry processing. In order to automatically generate tie points, we designed an image matching method considering LRO NAC images’ features of long strips and large data volumes. The terrain and smoothness constraints were introduced into the cost function of photoclinometry adjustment, excluding pixels in shadow areas. We used 61 LRO NAC images to generate mapping products covering an area of 400 km². The spatial resolution of the generated DOMs was 1 m/pixel, and the grid spacing of the derived DEMs was 1 m (close to the spatial resolution of the original images). The generated DOMs achieved a relative accuracy of better than 1 pixel. The geometric accuracy of the DEM derived from photoclinometry was consistent with the lunar orbiter laser altimeter (LOLA) DEM with a root mean square error of 0.97 m and an average error of 0.17 m. Full article

Since the landing on the lunar surface, the lunar regolith has begun to interact in different ways with landed elements, such as the wheels of a rover, astronaut suits, drills, and plants for extracting oxygen or manufacturing objects. Therefore, a strong effort has been required on Earth to fully characterise these kinds of interactions and regolith utilisation methods. This operation can only be performed by using regolith simulants, soils that are reproduced with the Earth’s rocks and minerals to match the real features. This article presents the main guidelines and tests for obtaining the properties of a generic simulant in terms of composition, physical and mechanical properties, solid–fluid interaction, and thermal properties. These parameters are needed for the designing and testing of payloads under development for planned lunar surface missions. The same tests can be performed on lunar, martian, or asteroid simulants/soils, both in laboratory and in situ. A case study is presented on the lunar simulant NU-LHT-2M, representative of the lunar highlands. The tests are performed in the context of an in situ resource utilisation (ISRU) process that aims to extract oxygen from the lunar regolith using a low-temperature carbothermal reduction process, highlighting the main regolith-related criticalities for an in situ demonstrator plant. Full article

Appropriate environmental sensing methods and visualization representations are crucial foundations for the in situ exploration of planets. In this paper, we developed specialized visualization methods to facilitate the rover’s interaction and decision-making processes, as well as to address the path-planning and obstacle-avoidance requirements for lunar polar region exploration and Mars exploration. To achieve this goal, we utilize simulated lunar polar regions and Martian environments. Among them, the lunar rover operating in the permanently shadowed region (PSR) of the simulated crater primarily utilizes light detection and ranging (LiDAR) for environmental sensing; then, we reconstruct a mesh using the Poisson surface reconstruction method. After that, the lunar rover’s traveling environment is represented as a red-green-blue (RGB) image, a slope coloration image, and a theoretical water content coloration image, based on different interaction needs and scientific objectives. For the rocky environment where the Mars rover is traveling, this paper enhances the display of the rocks on the Martian surface. It does so by utilizing depth information of the rock instances to highlight their significance for the rover’s path-planning and obstacle-avoidance decisions. Such an environmental sensing and enhanced visualization approach facilitates rover path-planning and remote–interactive operations, thereby enabling further exploration activities in the lunar PSR and Mars, in addition to facilitating the study and communication of specific planetary science objectives, and the production and display of basemaps and thematic maps. Full article

The International Lunar Research Station, to be established around 2030, will equip lunar rovers with robotic arms as constructors. Construction requires lunar soil and lunar rovers, for which rovers must go toward different waypoints without encountering obstacles in a limited time due to the short day, especially near the south pole. Traditional planning methods, such as uploading instructions from the ground, can hardly handle many rovers moving on the moon simultaneously with high efficiency. Therefore, we propose a new collaborative path-planning method based on deep reinforcement learning, where the heuristics are demonstrated by both the target and the obstacles in the artificial potential field. Environments have been randomly generated where small and large obstacles and different waypoints are created to collect resources, train the deep reinforcement learning agent to propose actions, and lead the rovers to move without obstacles, finish rovers’ tasks, and reach different targets. The artificial potential field created by obstacles and other rovers in every step affects the action choice of the rover. Information from the artificial potential field would be transformed into rewards in deep reinforcement learning that helps keep distance and safety. Experiments demonstrate that our method can guide rovers moving more safely without turning into nearby large obstacles or collision with other rovers as well as consuming less energy compared with the multi-agent A-Star path-planning algorithm with improved obstacle avoidance method. Full article

With the development of technology and methodologies, Raman spectrometers are becoming efficient candidate payloads for planetary materials characterizations in deep space exploration missions. The National Aeronautics and Space Administration (NASA) already deployed two Raman instruments, Super Cam and SHERLOC, onboard the Perseverance Rover in the Mars 2020 mission. In the ground test, the SHERLOC team found an axial offset (~720 μm) between the ACI (Autofocus Context Imager) and the spectrometer focus, which would obviously affect the acquired Raman intensity if not corrected. To eliminate this error and, more importantly, simplify the application of Raman instruments in deep space exploration missions, we propose an automatic focusing method wherein Raman signals are optimized during spectrum collection. We put forward a novel method that is realized by evaluating focus conditions numerically and searching for the extremum point as the final focal point. To verify the effectiveness of this method, we developed an Auto-focus Raman Probe (SDU-ARP) in our laboratory. This method provides a research direction for scenarios in which spectrometers cannot focus on a target using any other criterion. The utilization of this auto-focusing method can offer better spectra and fewer acquisitions in focusing procedure, and the spectrometer payload can be deployed in light-weight bodies (e.g., asteroids) or in poor illumination conditions (e.g., the permanently shadowed region in the Lunar south polar area) in deep space exploration missions. Full article

This research proposes a novel approach to global path and resource planning for lunar rovers. The proposed method incorporates a range of constraints, including static, time-variant, and path-dependent factors related to environmental conditions and the rover’s internal resource status. These constraints are integrated into a grid map as a penalty function, and a reinforcement learning-based framework is employed to address the resource constrained shortest path problem (RCSP). Compared to existing approaches referenced in the literature, our proposed method enables the simultaneous consideration of a broader spectrum of constraints. This enhanced flexibility leads to improved path search optimality. To evaluate the performance of our approach, this research applied the proposed learning architecture to lunar rover path search problems, generated based on real lunar digital elevation data. The simulation results demonstrate that our architecture successfully identifies a rover path while consistently adhering to user-defined environmental and rover resource safety criteria across all positions and time epochs. Furthermore, the simulation results indicate that our approach surpasses conventional methods that solely rely on environmental constraints. Full article

Water ice has been found in the permanently shadowed regions of impact craters around the lunar South Pole, which makes them ideal areas for in situ exploration missions. However, near the rim of impact craters, construction and exploration activities may cause slope instability. As a result, a better understanding of the shear strength of lunar soil under higher stress conditions is required. This paper mainly uses the finite element method to analyze slope stability to determine the position and shape of the slip surface and assess the safety factor. The height and gradient of the slope, the shear strength of lunar soil, and the lunar surface mission all influence the stability of the slope. We also analyze the soil mechanical properties of a soil slope adjacent to the traverse path of the Chang’E-4 Yutu-2 rover. Determining the stability of the slope at the lunar South Pole impact crater under various loading conditions will enhance the implementation of the lunar surface construction program. In this respect, this paper simulates a lunar mission landing at the Shackleton and Shoemaker craters and indicates that areas with higher cohesion lunar soil may be more stable for exploration in the more complex terrain of the South Pole. Full article

Over the previous two decades, a notable array of space exploration missions have been initiated with the primary aim of facilitating the return of both humans and robots from Earth to the moon. The significance of these endeavors cannot be emphasized enough as numerous entities, both public and private, from across the globe have invested substantial resources into this pursuit. Researchers have committed their efforts to addressing the challenges linked to lunar communication. Even with all of these efforts, only a few of the many suggested designs for communication and antennas on the moon have been evaluated and compared. These designs have also not been shared with the scientific community. To bridge this gap in the existing body of knowledge, this paper conducts a thorough review of lunar surface communication and the diverse antenna designs employed in lunar communication systems. This paper provides a summary of the findings presented in lunar surface communication research while also outlining the assorted challenges that impact lunar communication. Apart from various antenna designs reported in this field, based on their intended usage, two additional classifications are introduced: (a) mission-based antennas—utilized in actual lunar missions—and (b) research-based antennas—employed solely for research purposes. Given the critical need to comprehend and predict lunar conditions and antenna behaviors within those conditions, this review holds immense significance. Its relevance is particularly pronounced in light of the numerous upcoming lunar missions that have been announced. Full article

The illumination conditions of the lunar south pole region are complex due to the rugged terrain and very low solar elevation angles, posing significant challenges to the safety of lunar landing and rover explorations. High-spatial and temporal-resolution analyses of the illumination conditions in the south pole region are essential to support mission planning and surface operations. This paper proposes a method for illumination condition analysis in the lunar pole region using multi-temporal high-resolution orbital images with a pre-selected landing area of Chang’E-7 as the study area. Firstly, a database of historical multi-temporal high-resolution (0.69–1.97 m/pixel) orbital images, with associated image acquisition time, solar elevation angle, and azimuth angle, is established after preprocessing and registration. Secondly, images with the nearest solar elevation and azimuth at the planned time for mission operations are retrieved from the database for subsequent illumination condition analysis and exploration support. The differences in the actual solar positions at the mission moments from that of the nearest sun position image are calculated and their impact on illumination conditions is evaluated. Experimental results of the study area demonstrate that the constructed image database and the proposed illumination analysis method using multi-temporal images, with the assistance of DEM in a small number of cases, can effectively support the mission planning and operations for the Chang’E-7 mission in the near future. Full article

The article uses the Lunar QuickMap tool to analyze and select five highly promising cold microtraps on the Moon in terms of the size of the deposits they contain and their accessibility with the use of rovers and other wheeled vehicles. Since the thickness of the layer containing raw materials is subject to high uncertainty, three arbitrary scenarios for the value of this parameter were assumed: pessimistic (1 cm), nominal (5 cm), and optimistic (1 m). For the analyzed sites, a preliminary market valuation of the raw materials contained therein will be obtained at USD 74 billion; USD 370 billion; USD 7403 billion for the assumed pessimistic, normal, and optimistic scenarios, respectively. The article presents a business and technological perspective on the issue of space mining on the Moon. It is also a selected synthesis of the state of knowledge about space mining on the Moon. Full article

Autonomous lunar exploration is a complex task that requires the development of sophisticated algorithms to control the movement of lunar rovers in a challenging environment, based on visual feedback. To train and evaluate these algorithms, it is crucial to have access to both a simulation framework and data that accurately represent the conditions on the lunar surface, with the main focus on providing the visual fidelity necessary for computer vision algorithm development. In this paper, we present a lunar-orientated robotic simulation environment, developed using the Unity game engine, built on top of robot operating system 2 (ROS 2), which enables researchers to generate quality synthetic vision data and test their algorithms for autonomous perception and navigation of lunar rovers in a controlled environment. To demonstrate the versatility of the simulator, we present several use cases in which it is deployed on various efficient hardware platforms, including FPGA and Edge AI devices, to evaluate the performance of different vision-based algorithms for lunar exploration. In general, the simulation environment provides a valuable tool for researchers developing lunar rover systems. Full article