Robotic Planetary Exploration Research Articles

BASEPROD: The Bardenas Semi-Desert Planetary Rover Dataset

Dataset acquisitions devised specifically for robotic planetary exploration are key for the advancement, evaluation, and validation of novel perception, localization, and navigation methods in representative environments. Originating in the Bardenas semi-desert in July 2023, the data presented in this Data Descriptor is primarily aimed at Martian exploration and contains relevant rover sensor data from approximately 1.7km of traverses, a high-resolution 3D map of the test area, laser-induced breakdown spectroscopy recordings of rock samples along the rover path, as well as local weather data. In addition to optical cameras and inertial sensors, the rover features a thermal camera and six force-torque sensors. This setup enables, for example, the study of future localization, mapping, and navigation techniques in unstructured terrains for improved Guidance, Navigation, and Control (GNC). The main features of this dataset are the combination of scientific and engineering instrument data, as well as the inclusion of the thermal camera and force-torque sensors in particular.

Design and obstacle-crossing analysis of a four-link rocker-suspension planetary exploration robot

Abstract. At present, there are still many meteorite craters and boulders on the surface of Mars and the Moon that cannot be accessed by existing planetary exploration robots. To provide a solution to this issue, this paper proposes a four-link rocker-suspension planetary exploration robot that combines both the reliability and low complexity of wheeled rovers with competent terrain adaptability and obstacle-crossing performance. Relying on its special differential pitch device, the robot can adapt to fluctuations in terrain by using both active and passive modes. Moreover, the four-link rocker suspensions on both sides of the robot can increase the instantaneous rotation radius of the rockers when the robot climbs over obstacles. In this paper, using modelling and simulations, we demonstrate that the four-link rocker suspension can improve the robot's obstacle-crossing capability. The geometric and static conditions required for the robot to cross obstacles are derived and discussed, and numerical simulations are conducted to identify the maximum obstacle-crossing heights that satisfy different conditions. Finally, a physical prototype of the robot is developed.

Ground Interaction Models for Increased Autonomy of Planetary Exploration Systems

Future planetary exploration robots need to improve their autonomy to increase mission safety and efficiency. The presented concept achieves this by introducing the learning and usage of ground interaction models, which allow a more precise modelling of the robot’s mobility on different terrains. The idea is that a precise prediction of the expected performance will, on the one hand, allow an early detection of changed conditions and, on the other hand, enable a system to appropriately react on it. By classifying the traversed terrain, a robot gains the possibility to replan its path or to change its locomotion behavior to eventually optimize mission success. The paper provides details, on how the ground interaction models are trained, how the required data is collected, and how they are embedded into a physical simulator to use them online on the system.

Post-clustering Prioritization Framework for Autonomous Decision Making in the Absence of Ground Truth via Hypothetical Probing

A generic prioritization framework is introduced for addressing the problem of automated prioritization of region of interest or target selection. The framework is based on the assumption that clustering of preliminary data for preidentified regions or targets of interest within an operational area has already occurred, i.e., post-classification, and that the clustering quality can be expressed as an energy/objective function. Region or target of interest prioritization then means to rank regions or targets of interest according to their probability of changing the energy/objective function value upon subsequent hypothetical probing as opposed to actually conducted reexamination, i.e., thorough follow-up or in-situ measurements. The mathematical formalism for calculating these probabilities to contribute to this change of the energy/objective function value is introduced and validated through numerical simulations. Moreover, these probabilities can also be understood as a confidence-check of the classification, i.e., the pre-clustering of the preliminary data. The operation of the prioritization framework is independent of the algorithm used to pre-cluster the preliminary data, and supports autonomous decision-making. It is widely applicable across many scientific disciplines and areas, ranging from the microscopic to the macroscopic scale. Due to its ability to help maximize scientific return while optimizing resource utilization, it is particularly relevant in the context of resource-constrained autonomous robotic planetary exploration as it may extend the Remaining Useful Lifetime (RUL) – a key aspect in Prognostics and Health Management (PHM) – of space missions. On a more general, PHM-relevant level, the prioritization framework may provide an additional mechanism of identifying and correcting the maintenance status of system components to assist predictive maintenance or condition-based maintenance.

Modular Mechatronics Infrastructure for robotic planetary exploration assets in a field operation scenario

In 2021 the Modular Mechatronics Infrastructure (MMI) was introduced as a solution to reduce weight, costs, and development time in robotic planetary missions. With standardized interfaces and multi-functional elements, this modular approach is planned to be used more often in sustainable exploration activities on the Moon and Mars. The German multi-robot research project “Autonomous Robotic Networks to Help Modern Societies (ARCHES)” has explored this concept with the use of various collaborative robotic assets which have their capabilities extended by the MMI. Different scientific payloads, engineering infrastructure modules, and specific purpose tools can be integrated to and manipulated by a robotic arm and a standardized electromechanical docking-interface. Throughout the MMI’s design and implementation phase the performed preliminary tests confirmed that the different systems of the robotic cooperative team such as the Docking Interface System (DIS), the Power Management System (PMS), and the Data Communication System (DCS) functioned successfully. During the summer of 2022 a Demonstration Mission on Mount Etna (Sicily, Italy) was carried out as part of the ARCHES Project. This field scenario allowed the validation of the robotics systems in an analogue harsh environment and the confirmation of enhanced operations with the application of this modular method. Among the numerous activities performed in this volcanic terrain there are the efficient assembling of the Low Frequency Array (LOFAR) network, the energy-saving and reduced complexity of a detached Laser Induced Breakdown Spectroscopy (LIBS) module, and the uninterrupted powered operation between modules when switching between different power sources. The field data collected during this analogue campaign provided important outcomes for the modular robotics application. Modular and autonomous robots certainly benefit from their versatility, re-usability, less complex systems, reduced requirements for space qualification, and lower risks for the mission. These characteristics will ensure that long duration and complex robotic planetary endeavours are not as challenging as they used to be in the past.

Scientific exploration of challenging planetary analog environments with a team of legged robots

The interest in exploring planetary bodies for scientific investigation and in situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots’ inability to traverse steep slopes, unstructured terrain, and loose soil. In addition, current single-robot approaches only allow a limited exploration speed and a single set of skills. Here, we present a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. We equipped the robots with an efficient locomotion controller, a mapping pipeline for online and postmission visualization, instance segmentation to highlight scientific targets, and scientific instruments for remote and in situ investigation. Furthermore, we integrated a robotic arm on one of the robots to enable high-precision measurements. Legged robots can swiftly navigate representative terrains, such as granular slopes beyond 25°, loose soil, and unstructured terrain, highlighting their advantages compared with wheeled rover systems. We successfully verified the approach in analog deployments at the Beyond Gravity ExoMars rover test bed, in a quarry in Switzerland, and at the Space Resources Challenge in Luxembourg. Our results show that a team of legged robots with advanced locomotion, perception, and measurement skills, as well as task-level autonomy, can conduct successful, effective missions in a short time. Our approach enables the scientific exploration of planetary target sites that are currently out of human and robotic reach.

Golden wheel spider-inspired rolling robots for planetary exploration

Humans have been fascinated with nature and attempting to mimic what they see in nature for millennia. Using inspiration from organisms found in nature assists in developing a system that is well-suited for specific tasks and environments. This process is called bio-inspiration. When designing bio-inspired robots, locomotion is one of the most common sources of inspiration. Exploratory robots are often limited to wheels as the mode of transportation, but there are so many more options, each with its own benefits and uses. This work focuses on the design and development of various rolling robots for planetary exploration. Specifically, these rolling robots are being designed for the exploration of the Martian surface. The main source of inspiration for these rovers is the Golden Wheel Spider. This spider is known for its wind-assisted rolling capabilities, allowing it to traverse sand dunes with minimal effort quickly. In addition to prototypes, a dynamical model of the conceptual Spider Rolling Robot (SRR) has been developed. Studies have been done to determine just how much the wind will be able to assist the SRR under realistic conditions on the Martian surface. Finally, CoppeliaSim simulations have been built to test and compare various model designs to find the most effective form of the SRR.

Design and Analysis of All-Terrain Differential-Driven Caterpillar-Wheeled Based Unmanned Fire Extinguisher Robot

The usage of wheeled robots in service robots such as planetary exploration robots, pick-and-place robots, cleaning robots, surveillance robots, etc., is continuously increasing day by day. The primary purpose of these service robots is to reduce human resources and minimize human life risk in a hazardous environment. Therefore, in this article, the authors purpose and design the all-terrain differential-driven caterpillar-wheeled based unmanned Fire Extinguisher Robot (FER), which can detect and monitor the fire by using gas (smoke) sensor and temperature sensor. Also, it can extinguish the fire by spreading the fire extinguisher gas. The proposed unmanned FER has been divided into the two assembled units, one unit drives the FER, and another unit is for spreading the fire extinguisher gas through the nozzle of the cylinder. The driving unit of unmanned FER consists of six DC geared motors, two dual DC motor drivers, caterpillar driving wheels, Arduino MEGA microcontroller, Bluetooth module, gas sensor, temperature sensor, and rechargeable lithium-polymer (LiPo) battery. Next, the one DC motor connected with a motor driver controls the fire extinguisher gas cylinder's open and close valve through a Bluetooth signal from an android phone. The specially designed chassis and caterpillar driving wheel arrangement help the FER to travel in any terrain, including stair climbing. Real-time experimental tests have been carried out on the designed unmanned FER during the fire extinguishing process to prove the effectiveness of the developed FER.

Simulation of the Landing Buffer of a Three-Legged Jumping Robot

In recent years, the research of planetary exploration robots has become an active field. The jumping robot has become a hot spot in this field. This paper presents a work modelling and simulating a three-legged jumping robot, which has a powerful force, high leaping performance, and good flexibility. In particular, the jumping of the robot was simulated and the landing buffer of the robot was analyzed. Because this jumping robot lacks landing buffer, this paper verifies a method of absorbing landing kinetic energy to improve landing stability and storing it as the energy for the next jump in the simulation. Through the landing simulation, the factors affecting the landing energy absorption are identified. Moreover, the simulation experiment verifies that the application of the intermediate axis theorem helps to absorb more energy and adjust the landing attitude of the robot. The simulation results in this paper can be applied to the optimal design of robot prototypes and provide a theoretical basis for subsequent research.

An autonomous navigation approach for unmanned vehicle in outdoor unstructured terrain with dynamic and negative obstacles

AbstractAt present, the study on autonomous unmanned ground vehicle navigation in an unstructured environment is still facing great challenges and is of great significance in scenarios where search and rescue robots, planetary exploration robots, and agricultural robots are needed. In this paper, we proposed an autonomous navigation method for unstructured environments based on terrain constraints. Efficient path search and trajectory optimization on octree map are proposed to generate trajectories, which can effectively avoid various obstacles in off-road environments, such as dynamic obstacles and negative obstacles, to reach the specified destination. We have conducted empirical experiments in both simulated and real environments, and the results show that our approach achieved superior performance in dynamic obstacle avoidance tasks and mapless navigation tasks compared to the traditional 2-dimensional or 2.5-dimensional navigation methods.

The Need for and Feasibility of Alternative Ground Robots to Traverse Sandy and Rocky Extraterrestrial Terrain

Robotic spacecrafts have helped expand the reach for many planetary exploration missions. Most ground mobile planetary exploration robots use wheeled or modified wheeled platforms. Although extraordinarily successful at completing intended mission goals, because of the limitations of wheeled locomotion, they have been largely limited to benign, solid terrain and avoided extreme terrain with loose soil/sand and large rocks. Unfortunately, such challenging terrain is often scientifically interesting for planetary geology. Although many animals traverse such terrain at ease, robots have not matched their performance and robustness. This is in major part due to a lack of fundamental understanding of how effective locomotion can be generated from controlled interaction with complex terrain on the same level of flight aerodynamics and underwater vehicle hydrodynamics. Early fundamental understanding of legged and limbless locomotor–ground interaction has already enabled stable and efficient bioinspired robot locomotion on relatively flat ground with small obstacles. Recent progress in the new field of terradynamics of locomotor–terrain interaction begins to reveal the principles of bioinspired locomotion on loose soil/sand and over large obstacles. Multilegged and limbless platforms using terradynamics insights hold the promise for serving as robust alternative platforms for traversing extreme extraterrestrial terrain and expanding the reach in planetary exploration.

On the role of feature and signal selection for terrain learning in planetary exploration robots

AbstractIncreasing the terrain awareness of planetary exploration rovers is one key technology for future space robotics to successfully accomplish long‐distance and long‐duration missions. In contrast to most of the existing algorithms that use visual or depth data for terrain classification, the approach presented in this study tackles the problem using proprioceptive sensing, for example, vibration or force measurements. The underlying assumption is that these signals, being directly modulated by the terrain properties, are well descriptive of a given surface. Therefore, terrain signature can be inferred via learning algorithms that are trained on either the signals directly or a signal‐derived feature set. Following the latter approach, first, a physics‐based signal augmentation process is presented that aims at maximizing the information content. Then, a feature selection algorithm based on a scoring system and an iterative search is developed to decrease the computational cost while preserving high classification accuracy. The resulting most informative feature subspace can be used to train a support vector machine (SVM) classifier. For comparison, the time histories of the selected proprioceptive signals are used to train a deep convolutional neural network (CNN). Results obtained from real experiments using the SherpaTT rover confirm that proprioceptive sensing is effective in predicting terrain type with an accuracy higher than 90% for both algorithms in generalization tasks. When the two learning approaches are contrasted in extrapolation problems, for example, predicting observations acquired at previously unseen velocity or terrain, CNN outperforms the standard SVM. Furthermore, CNN holds the additional advantage of learning features automatically from signal spectrograms, reducing the need of a priori knowledge at the expense of higher computational efforts.

Recent research and development activities on space robotics and AI

Deep space exploration missions have received a lot of attention in the world, such as the moon, Mars, asteroids for scientific observation and human activities. Recently, not only space agencies but also industries or universities have earnestly studied and developed lunar or planetary robots for lunar or planetary exploration. International cooperative missions are also under discussion including human lunar exploration. Space robotics including Al is a key technology for planetary exploration as well as orbital service. Future space programs require space AI and robotics technology to construct, repair and maintain satellites and space structures in orbit. This paper introduces recent space missions and surveys hot topics on new research activities and developed technology for the near future missions.

Energy Dissipation during Surface Interaction of an Underactuated Robot for Planetary Exploration

The article summarizes research on essential contributors to energy dissipation in an actuator for an exemplary planetary exploration hopping robot. It was demonstrated that contact dynamics could vary significantly depending on the surface type. As a result, regolith is a significant uncertainty factor to the control loop and plays a significant contribution in the control system development of future planetary exploration robots. The actual prototype of the actuating mechanism was tested on a reference surface and then compared with various surfaces (i.e., Syar, quartz sand, expanded clay, and quartz aggregate) to estimate the dissipation of the energy in the initial phase of hopping. Test outcomes are compared with multibody analysis. The research enhances trajectory planning and adaptive control of future hopping robots by determining three significant types of energy losses in the system and, most importantly, determining energy dissipation coefficients in contact with the various surfaces (i.e., from 4% to 53% depending on the surface type). The actual step-by-step methodology is proposed to analyze energy dissipation aspects for a limited number of runs, as it is a case for space systems.

High-adaption locomotion with stable robot body for planetary exploration robot carrying potential instruments on unstructured terrain

There is a strong demand for Planetary Exploration Mobile robots (PEMRs) that have the capability of the traversability, stability, efficiency and high load while tackling the specialized tasks on planet surface. In this paper, an electric parallel wheel-legged hexapod robot which has high-adaption locomotion on the unstructured terrain is presented. Also, the hybrid control framework, which enables robot to stably carry the heavy loads as well as to traverse the uneven terrain by utilizing both legged and wheeled locomotion, is also proposed. Based on this framework, robot controls the multiple DOF leg for performing high-adaption locomotion to negotiate obstacles via Gait Generator (GG). Additionally, by using Whole-Body Control (WBC) of framework, robot has the capability of flexibly accommodating the uneven terrain by Attitude Control (AC) kinematically adjusting the length of legs like an active suspension system, and by Force/torque Balance Control (FBC) equally distributing the Ground Reaction Force (GRF) to maintain a stable body. The simulation and experiment are employed to validate the proposed framework with the physical system in the planetary analog environments. Particularly, to smoothly demonstrate the performance of robot transporting heavy loads, the experiment of carrying 3-person load of about 240 kg is deployed.

Definition and use of functional analogues in planetary exploration

The practical limitations inherent to human and robotic planetary exploration necessitate the development of specific protocols and methods. This non-standard approach requires testing and validation phases in order to optimise instrumental setups and improve data interpretation; this can occur prior to, during, or even after a mission. Flight instruments, and/or their spare models, may be evaluated using relevant terrestrial materials and/or locations. These materials are called analogues: “analogue sites” for large-scale locations, and “analogue samples” for smaller-scale materials. Depending on the scientific domain, the word “analogue” may carry different meanings but is invariably used to denote objects having compositions and/or physical properties similar to specific extraterrestrial objects. However, due to the variability in composition and properties of natural materials, there are always – inevitably – some differences between the analogue and the object(s) to which it refers. In analogue studies, it is, thus, important to focus on the specific properties that need to be imitated and to consider analogue properties rather than analogue sites or samples alone. Here, we introduce the concept of “functional analogues”. We first make an overview of the different types of analogues and sort them according to their utility. We then describe how different types of functional analogues can be used throughout the timeline of space missions, from the evaluation of different methods in the definition of a mission to understanding the results acquired by probes exploring extraterrestrial bodies. Finally, logical pathways are outlined that facilitate the selection of the best-suited functional analogue(s) according to their intended use and taking into account practical limitations.

Quantitative analysis of binary and ternary organo-mineral solid dispersions by Raman spectroscopy for robotic planetary exploration missions on Mars.

The Mars 2020 and ExoMars 2022, rover-based missions are specifically dedicated to the search for evidence of life and will both utilise Raman spectrometers on the surface of Mars. Raman spectroscopy is indeed a valuable analytical technique for planetary exploration that enables in situ characterisation of rocks and soils collected directly from the surface or retrieved as cores and subsequently crushed when extracted from the subsurface with a drill. On Mars, the miniaturised spectrometers will interrogate ancient geological deposits, in order to try and identify hydrated or aqueously altered minerals and organic matter to assess the habitability of Mars. While the identification of relevant hydrous minerals and organic components is the primary analytical objective of the missions, quantifying their abundances would be of particular significance for interpreting past geological conditions (e.g. formation or alteration processes) and for ascertaining the putative presence of biosignatures. Therefore, we have developed quantitative models that enable the quantification of both mineral proportions from crushed mixtures of geological components and spiked mixtures containing organic analytes dispersed in mineral matrices. Based on data normalisation with appropriate standards (internal and external), we demonstrate that robust quantitative models can be (1) applied for solid dispersions of various complexities relevant to planetary exploration; and (2) applied to different Raman set-ups, including an instrument representative of the ExoMars Raman Laser Spectrometer. With important Raman-active minerals (calcite, gypsum, baryte, quartz), we demonstrate that using a correction factor Fϕ2/ϕ1, based on the ratio of apparent Raman scattering coefficients, the relative proportion of minerals in binary mixtures can be accurately determined. Regarding the organics, evaluated in clay-rich sediments (Fe-smectite) and crushed rocks of coarse-grained fraction (>100μm), we establish calibration curves in the concentration range 2-20 wt% for non-resonant compounds (L-cysteine, phthalic acid, adenine) and even lower (<1 wt%) for pre-resonant anthracene. Despite large levels of heterogeneity, the Raman analyses of these solid dispersions verify that quantitative Raman analyses can be performed in the context of robotic exploration studies.

Wheel Slip Detection for Electric Drive in Planetary Exploration Vehicles

This article illustrates a technique for tracking longitudinal wheel slips in real time using an embedded microcontroller to map current consumption against real-time current consumed by the engine. This system can be used and operated separately of each other on more than one wheel. To detect wheel slippage, a predefined slip curve mapped to a specific DC electric motor is mapped against the current consumed by the same operational motors. This paper also recommends a convenient control algorithm to calculate its slippage of the wheel in real time. This approach is implemented using distinct load and terrain on a planetary exploration robot.

Modular Field Robots for Extraterrestrial Exploration

Modular design methodology enables rapid reconfigurability for functional changes, robustness to failures and space utilisation for transportation. In the case of planetary exploration robots, there is promise in modular robots that are able to reconfigure themselves for exploration of unknown terrains. This paper presents a design and controller architecture for modular field robots that can be rapidly assembled in a variety of functional configurations. A key challenge of building a functional robot out of modular units is the ability to seamlessly add, remove and replace individual units to enable functional improvements as well as adapt to terrain requirements. We present a representative modular wheel design and a distributed controller architecture able to create a range of bespoke multi-wheeled configurations capable of traversal on a variety of terrains during simulated failure scenarios. The self-contained wheeled unit has energy, computation communication, and actuation modules and does not require any modification or physical customization in the field during deployment enabling a seamless plug and play behaviour. The hierarchical control structure runs a body controller node that decomposes a whole body motion requested from a higher level planner to generate a sequence of actuation goals for each of the modules, while a local controller node running on each of the modules ensures that the desired actuation is adapted to the configuration, load and terrain characteristics.

An Efficient Minimum-Time Cooperative Task Planning Algorithm for Serving Robots and Operators

SUMMARYWe establish an efficient minimum-time cooperative task planning algorithm for robots and operators to serve clients. This problem is an extension of the multiple traveling salesman problem and the vehicle routing problem with synchronization constraints, but it is more difficult due to the cooperative tasks of the robots and operators. To find the exact minimum-time task plan with a small tree size, we propose an efficient branch-and-bound with a good initial tree and keen complementary heuristics. Our algorithm is also effective as an approximate algorithm for the many clients problem within the capacity of the computer used. The efficiency of our algorithm is revealed via case studies: telemedical service robots and planetary exploration robots.