A Deep Learning Approach to Lunar Rover Global Path Planning Using Environmental Constraints and the Rover Internal Resource Status.

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.

Modeling of Cooperative Robotic Systems and Predictive Control Applied to Biped Robots and UAV-UGV Docking with Task Prioritization.

This paper studies a cooperative modeling framework to reduce the complexity in deriving the governing dynamical equations of complex systems composed of multiple bodies such as biped robots and unmanned aerial and ground vehicles. The approach also allows for an optimization-based trajectory generation for the complex system. This work also studies a fast-slow model predictive control strategy with task prioritization to perform docking maneuvers on cooperative systems. The method allows agents and a single agent to perform a docking maneuver. In addition, agents give different priorities to a specific subset of shared states. In this way, overall degrees of freedom to achieve the docking task are distributed among various subsets of the task space. The fast-slow model predictive control strategy uses non-linear and linear model predictive control formulations such that docking is handled as a non-linear problem until agents are close enough, where direct transcription is calculated using the Euler discretization method. During this phase, the trajectory generated is tracked with a linear model predictive controller and addresses the close proximity motion to complete docking. The trajectory generation and modeling is demonstrated on a biped robot, and the proposed MPC framework is illustrated in a case study, where a quadcopter docks on a non-holonomic rover using a leader-follower topology.

Technology Selection for Inline Topography Measurement with Rover-Borne Laser Spectrometers.

This work studies enhancing the capabilities of compact laser spectroscopes integrated into space-exploration rovers by adding 3D topography measurement techniques. Laser spectroscopy enables the in situ analysis of sample composition, aiding in the understanding of the geological history of extraterrestrial bodies. To complement spectroscopic data, the inclusion of 3D imaging is proposed to provide unprecedented contextual information. The morphological information aids material characterization and hence the constraining of rock and mineral histories. Assigning height information to lateral pixels creates topographies, which offer a more complete spatial dataset than contextual 2D imaging. To aid the integration of 3D measurement into future proposals for rover-based laser spectrometers, the relevant scientific, rover, and sample constraints are outlined. The candidate 3D technologies are discussed, and estimates of performance, weight, and power consumptions guide the down-selection process in three application examples. Technology choice is discussed from different perspectives. Inline microscopic fringe-projection profilometry, incoherent digital holography, and multiwavelength digital holography are found to be promising candidates for further development.

Investigating the Impact of Lunar Rover Structure and Lunar Surface Characteristics on Antenna Performance.

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.

Performance Analysis of Relative GPS Positioning for Low-Cost Receiver-Equipped Agricultural Rovers.

Global navigation satellite systems (GNSSs) became an integral part of all aspects of our lives, whether for positioning, navigation, or timing services. These systems are central to a range of applications including road, aviation, maritime, and location-based services, agriculture, and surveying. The Global Positioning System (GPS) Standard Position Service (SPS) provides position accuracy up to 10 m. However, some modern-day applications, such as precision agriculture (PA), smart farms, and Agriculture 4.0, have demanded navigation technologies able to provide more accurate positioning at a low cost, especially for vehicle guidance and variable rate technology purposes. The Society of Automotive Engineers (SAE), for instance, through its standard J2945 defines a maximum of 1.5 m of horizontal positioning error at 68% probability (1σ), aiming at terrestrial vehicle-to-vehicle (V2V) applications. GPS position accuracy may be improved by addressing the common-mode errors contained in its observables, and relative GNSS (RGNSS) is a well-known technique for overcoming this issue. This paper builds upon previous research conducted by the authors and investigates the sensitivity of the position estimation accuracy of low-cost receiver-equipped agricultural rovers as a function of two degradation factors that RGNSS is susceptible to: communication failures and baseline distances between GPS receivers. The extended Kalman filter (EKF) approach is used for position estimation, based on which we show that it is possible to achieve 1.5 m horizontal accuracy at 68% probability (1σ) for communication failures up to 3000 s and baseline separation of around 1500 km. Experimental data from the Brazilian Network for Continuous Monitoring of GNSS (RBMC) and a moving agricultural rover equipped with a low-cost GPS receiver are used to validate the analysis.

Vibration-Based Recognition of Wheel-Terrain Interaction for Terramechanics Model Selection and Terrain Parameter Identification for Lugged-Wheel Planetary Rovers.

Identifying terrain parameters is important for high-fidelity simulation and high-performance control of planetary rovers. The wheel-terrain interaction classes (WTICs) are usually different for rovers traversing various types of terrain. Every terramechanics model corresponds to its wheel-terrain interaction class (WTIC). Therefore, for terrain parameter identification of the terramechanics model when rovers traverse various terrains, terramechanics model switching corresponding to the WTIC needs to be solved. This paper proposes a speed-independent vibration-based method for WTIC recognition to switch the terramechanics model and then identify its terrain parameters. In order to switch terramechanics models, wheel-terrain interactions are divided into three classes. Three vibration models of wheels under three WTICs have been built and analyzed. Vibration features in the models are extracted and non-dimensionalized to be independent of wheel speed. A vibration-feature-based recognition method of the WTIC is proposed. Then, the terrain parameters of the terramechanics model corresponding to the recognized WTIC are identified. Experiment results obtained using a Planetary Rover Prototype show that the identification method of terrain parameters is effective for rovers traversing various terrains. The relative errors of estimated wheel-terrain interaction force with identified terrain parameters are less than 16%, 12%, and 9% for rovers traversing hard, gravel, and sandy terrain, respectively.

A Review of Lunar Communications and Antennas: Assessing Performance in the Context of Propagation and Radiation.

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.

Development of a high-throughput field phenotyping rover optimized for size-limited breeding fields as open-source hardware.

Phenotyping is a critical process in plant breeding, especially when there is an increasing demand for streamlining a selection process in a breeding program. Since manual phenotyping has limited efficiency, high-throughput phenotyping methods are recently popularized owing to progress in sensor and image processing technologies. However, in a size-limited breeding field, which is common in Japan and other Asian countries, it is challenging to introduce large machinery in the field or fly unmanned aerial vehicles over the field. In this study, we developed a ground-based high-throughput field phenotyping rover that could be easily introduced to a field regardless of the scale and location of the field even without special facilities. We also made the field rover open-source hardware, making its system available to public for easy modification, so that anyone can build one for their own use at a low cost. The trial run of the field rover revealed that it allowed the collection of detailed remote-sensing images of plants and quantitative analyses based on the images. The results suggest that the field rover developed in this study could allow efficient phenotyping of plants especially in a small breeding field.

Semantic Terrain Segmentation in the Navigation Vision of Planetary Rovers-A Systematic Literature Review.

Background: The planetary rover is an essential platform for planetary exploration. Visual semantic segmentation is significant in the localization, perception, and path planning of the rover autonomy. Recent advances in computer vision and artificial intelligence brought about new opportunities. A systematic literature review (SLR) can help analyze existing solutions, discover available data, and identify potential gaps. Methods: A rigorous SLR has been conducted, and papers are selected from three databases (IEEE Xplore, Web of Science, and Scopus) from the start of records to May 2022. The 320 candidate studies were found by searching with keywords and bool operators, and they address the semantic terrain segmentation in the navigation vision of planetary rovers. Finally, after four rounds of screening, 30 papers were included with robust inclusion and exclusion criteria as well as quality assessment. Results: 30 studies were included for the review, and sub-research areas include navigation (16 studies), geological analysis (7 studies), exploration efficiency (10 studies), and others (3 studies) (overlaps exist). Five distributions are extendedly depicted (time, study type, geographical location, publisher, and experimental setting), which analyzes the included study from the view of community interests, development status, and reimplementation ability. One key research question and six sub-research questions are discussed to evaluate the current achievements and future gaps. Conclusions: Many promising achievements in accuracy, available data, and real-time performance have been promoted by computer vision and artificial intelligence. However, a solution that satisfies pixel-level segmentation, real-time inference time, and onboard hardware does not exist, and an open, pixel-level annotated, and the real-world data-based dataset is not found. As planetary exploration projects progress worldwide, more promising studies will be proposed, and deep learning will bring more opportunities and contributions to future studies. Contributions: This SLR identifies future gaps and challenges by proposing a methodical, replicable, and transparent survey, which is the first review (also the first SLR) for semantic terrain segmentation in the navigation vision of planetary rovers.

Value Iteration Networks with Double Estimator for Planetary Rover Path Planning.

Path planning technology is significant for planetary rovers that perform exploration missions in unfamiliar environments. In this work, we propose a novel global path planning algorithm, based on the value iteration network (VIN), which is embedded within a differentiable planning module, built on the value iteration (VI) algorithm, and has emerged as an effective method to learn to plan. Despite the capability of learning environment dynamics and performing long-range reasoning, the VIN suffers from several limitations, including sensitivity to initialization and poor performance in large-scale domains. We introduce the double value iteration network (dVIN), which decouples action selection and value estimation in the VI module, using the weighted double estimator method to approximate the maximum expected value, instead of maximizing over the estimated action value. We have devised a simple, yet effective, two-stage training strategy for VI-based models to address the problem of high computational cost and poor performance in large-size domains. We evaluate the dVIN on planning problems in grid-world domains and realistic datasets, generated from terrain images of a moon landscape. We show that our dVIN empirically outperforms the baseline methods and generalize better to large-scale environments.

Visual SLAM-Based Robotic Mapping Method for Planetary Construction.

With the recent discovery of water-ice and lava tubes on the Moon and Mars along with the development of in-situ resource utilization (ISRU) technology, the recent planetary exploration has focused on rover (or lander)-based surface missions toward the base construction for long-term human exploration and habitation. However, a 3D terrain map, mostly based on orbiters' terrain images, has insufficient resolutions for construction purposes. In this regard, this paper introduces the visual simultaneous localization and mapping (SLAM)-based robotic mapping method employing a stereo camera system on a rover. In the method, S-PTAM is utilized as a base framework, with which the disparity map from the self-supervised deep learning is combined to enhance the mapping capabilities under homogeneous and unstructured environments of planetary terrains. The overall performance of the proposed method was evaluated in the emulated planetary terrain and validated with potential results.

Measuring the Normal Stress Distribution Acting on a Locked-Wheel of Push-Pull Locomotion Rovers via a Wheel Sensor System.

The resistance force generated when the locked-wheel acts on the soil is critical for deciding the traveling performance of push-pull locomotion. The resistance force depends on the tangential force of the sliding soil wedge beneath the wheel, and the tangential force depends on the forces of the soil and the wheel perpendicular to the tangential direction. Hence, the normal stress distribution of the locked-wheel can affect the resistance force. Previous studies indicated different insights that describe either a uniform or non-uniform shape of the normal stress distribution. The distribution of the locked-wheel still needs to be examined experimentally. This study measured the normal stress distribution using the wheel sensor system, and the variation of the contact area and slip surface beneath the wheel were also observed in PIV analysis. Those results showed that the normal stress distribution was non-uniform along the wheel contact area, and the change of the distribution was confirmed with the change of the contact area and slip surface. Then, the resistance force calculated by a preliminary model based on the measured data was compared with the total resistance force of the wheel measured by a separate sensor. This comparison provided a theoretical consideration for the measured data.

Mars Science Laboratory Observations of Chloride Salts in Gale Crater, Mars.

The Mars Science Laboratory Curiosity rover is traversing a sequence of stratified sedimentary rocks in Gale crater that contain varied eolian, fluviodeltaic, and lake deposits, with phyllosilicates, iron oxides, and sulfate salts. Here, we report the chloride salt distribution along the rover traverse. Chlorine is detected at low levels (<3 wt.%) in soil and rock targets with multiple MSL instruments. Isolated fine-scale observations of high chlorine (up to ≥15 wt.% Cl), detected using the ChemCam instrument, are associated with elevated Na2O and interpreted as halite grains or cements in bedrock. Halite is also interpreted at the margins of veins and in nodular, altered textures. We have not detected halite in obvious evaporitic layers. Instead, its scattered distribution indicates that chlorides emplaced earlier in particular members of the Murray formation were remobilized and reprecipitated by later groundwaters within Murray formation mudstones and in diagenetic veins and nodules.

Uncertainty-Based Vibration/Gyro Composite Planetary Terrain Mapping.

Accurate perception of the detected terrain is a precondition for the planetary rover to perform its own mission. However, terrain measurement based on vision and LIDAR is subject to environmental changes such as strong illumination and dust storms. In this paper, considering the influence of uncertainty in the detection process, a vibration/gyro coupled terrain estimation method based on multipoint ranging information is proposed. The terrain update model is derived by analyzing the measurement uncertainty and motion uncertainty. Combined with Clearpath Jackal unmanned vehicle-the terrain mapping accuracy test based on ROS (Robot Operating System) simulation environment-indoor Optitrack auxiliary environment and outdoor soil environment was completed. The results show that the proposed algorithm has high reconstruction ability for a given scale terrain. The reconstruction accuracy in the above test environments is within 1 cm, 2 cm, and 6 cm, respectively.

Deep Multi-Layer Perception Based Terrain Classification for Planetary Exploration Rovers.

Accurate classification and identification of the detected terrain is the basis for the long-distance patrol mission of the planetary rover. But terrain measurement based on vision and radar is subject to conditions such as light changes and dust storms. In this paper, under the premise of not increasing the sensor load of the existing rover, a terrain classification and recognition method based on vibration is proposed. Firstly, the time-frequency domain transformation of vibration information is realized by fast Fourier transform (FFT), and the characteristic representation of vibration information is given. Secondly, a deep neural network based on multi-layer perception is designed to realize classification of different terrains. Finally, combined with the Jackal unmanned vehicle platform, the XQ unmanned vehicle platform, and the vibration sensor, the terrain classification comparison test based on five different terrains was completed. The results show that the proposed algorithm has higher classification accuracy, and different platforms and running speeds have certain influence on the terrain classification at the same time, which provides support for subsequent practical applications.

The Scientific Information Model of Chang'e-4 Visible and Near-IR Imaging Spectrometer (VNIS) and In-Flight Verification.

The Chang'e-4 (CE-4) lunar rover, equipped with a visible and near-IR imaging spectrometer (VNIS) based on acousto-optic tunable filter spectroscopy, was launched to the far side of the moon on December 8, 2018. The detection band of the VNIS ranges from 0.45 to 2.4 µm. Because of the weak reflection of infrared radiation from the lunar surface, a static electronic phase-locked acquisition method is adopted in the infrared channel for signal amplification. In this paper, full-link simulations and modeling are conducted on the infrared channel information flow of the instrument. The signal characteristics of the VNIS are analyzed in depth, and the signal to noise ratio (SNR) prediction and laboratory verification are presented. On 4 January 2019, the VNIS started working successfully and acquired high-resolution spectrum data of the far side of the moon for the first time. Through analysis we have found that the SNR ratio is in line with our predictions, and the data obtained by VNIS in orbit are consistent with the information model proposed in this paper.

Volcanic history of the Imbrium basin: A close-up view from the lunar rover Yutu.

We report the surface exploration by the lunar rover Yutu that landed on the young lava flow in the northeastern part of the Mare Imbrium, which is the largest basin on the nearside of the Moon and is filled with several basalt units estimated to date from 3.5 to 2.0 Ga. The onboard lunar penetrating radar conducted a 114-m-long profile, which measured a thickness of ∼5 m of the lunar regolith layer and detected three underlying basalt units at depths of 195, 215, and 345 m. The radar measurements suggest underestimation of the global lunar regolith thickness by other methods and reveal a vast volume of the last volcano eruption. The in situ spectral reflectance and elemental analysis of the lunar soil at the landing site suggest that the young basalt could be derived from an ilmenite-rich mantle reservoir and then assimilated by 10-20% of the last residual melt of the lunar magma ocean.

Determining best practices in reconnoitering sites for habitability potential on Mars using a semi-autonomous rover: A GeoHeuristic Operational Strategies Test.

We tested science operations strategies developed for use in remote mobile spacecraft missions, to determine whether reconnoitering a site of potential habitability prior to in-depth study (a walkabout-first strategy) can be a more efficient use of time and resources than the linear approach commonly used by planetary rover missions. Two field teams studied a sedimentary sequence in Utah to assess habitability potential. At each site one team commanded a human "rover" to execute observations and conducted data analysis and made follow-on decisions based solely on those observations. Another team followed the same traverse using traditional terrestrial field methods, and the results of the two teams were compared. Test results indicate that for a mission with goals similar to our field case, the walkabout-first strategy may save time and other mission resources, while improving science return. The approach enabled more informed choices and higher team confidence in choosing where to spend time and other consumable resources. The walkabout strategy may prove most efficient when many close sites must be triaged to a smaller subset for detailed study or sampling. This situation would arise when mission goals include finding, identifying, characterizing or sampling a specific material, feature or type of environment within a certain area.

UNDR ROVER - a fast and accurate variant caller for targeted DNA sequencing.

BACKGROUND: Previously, we described ROVER, a DNA variant caller which identifies genetic variants from PCR-targeted massively parallel sequencing (MPS) datasets generated by the Hi-Plex protocol. ROVER permits stringent filtering of sequencing chemistry-induced errors by requiring reported variants to appear in both reads of overlapping pairs above certain thresholds of occurrence. ROVER was developed in tandem with Hi-Plex and has been used successfully to screen for genetic mutations in the breast cancer predisposition gene PALB2. ROVER is applied to MPS data in BAM format and, therefore, relies on sequence reads being mapped to a reference genome. In this paper, we describe an improvement to ROVER, called UNDR ROVER (Unmapped primer-Directed ROVER), which accepts MPS data in FASTQ format, avoiding the need for a computationally expensive mapping stage. It does so by taking advantage of the location-specific nature of PCR-targeted MPS data. RESULTS: The UNDR ROVER algorithm achieves the same stringent variant calling as its predecessor with a significant runtime performance improvement. In one indicative sequencing experiment, UNDR ROVER (in its fastest mode) required 8-fold less sequential computation time than the ROVER pipeline and 13-fold less sequential computation time than a variant calling pipeline based on the popular GATK tool. UNDR ROVER is implemented in Python and runs on all popular POSIX-like operating systems (Linux, OS X). It requires as input a tab-delimited format file containing primer sequence information, a FASTA format file containing the reference genome sequence, and paired FASTQ files containing sequence reads. Primer sequences at the 5' end of reads associate read-pairs with their targeted amplicon and, thus, their expected corresponding coordinates in the reference genome. The primer-intervening sequence of each read is compared against the reference sequence from the same location and variants are identified using the same algorithm as ROVER. Specifically, for a variant to be 'called' it must appear at the same location in both of the overlapping reads above user-defined thresholds of minimum number of reads and proportion of reads. CONCLUSIONS: UNDR ROVER provides the same rapid and accurate genetic variant calling as its predecessor with greatly reduced computational costs.

Indicators and Methods to Understand Past Environments from ExoMars Rover Drills.

Great advances are expected during the analysis of drilled material acquired from 2 m depth by ExoMars rover, supported by the comparison to local context, and the joint use of different instruments. Textural information might be less detailed relatively to what is usually obtained at outcrops during classical geological field work on the Earth, partly because of the lack of optical imaging of the borehole wall and also because the collected samples are crushed. However sub-mm scale layering and some other sedimentary features might be identified in the borehole wall observations, or in the collected sample prior to crushing, and also at nearby outcrops. The candidate landing sites provide different targets and focus for research: Oxia Planum requires analysis of phyllosilicates and OH content, at Mawrth Vallis the layering of various phyllosilicates and the role of shallow-subsurface leaching should be emphasized. At Aram Dorsum the particle size and fluvial sedimentary features will be interesting. Hydrated perchlorates and sulphates are ideal targets possibly at every landing sites because of OH retention, especially if they are mixed with smectites, thus could point to even ancient wet periods. Extensive use of information from the infrared wall scanning will be complemented for geological context by orbital and rover imaging of nearby outcrops. Information from the context is especially useful to infer the possible action of past H2O. Separation of the ice and liquid water effects will be supported by cation abundance and sedimentary context. Shape of grains also helps here, and composition of transported grains points to the weathering potential of the environment in general. The work on Mars during the drilling and sample analysis will provide brand new experience and knowledge for future missions.