Rover System Research Articles

Autonomous Vehicle for Fire detecting and Extinguishing

— Our project presents an innovative solution for fire detection and extinguishing through an autonomous rover system. Leveraging fire sensors integrated with a node MCU, the system swiftly identifies fire outbreaks and transmits alerts to the rover via the ThingSpeak cloud platform. Upon receipt of the alert, the rover activates a buzzer for immediate local notification and dispatches alerts through a dedicated mobile application, ensuring rapid response from relevant personnel. Employing a line follower mechanism, the rover autonomously navigates towards the fire-affected area. Equipped with a water spraying system, the rover efficiently extinguishes flames, minimizing water wastage and enhancing firefighting effectiveness. This approach significantly reduces response time, enhancing safety across diverse environments. The system's ability to optimize resource utilization and automate firefighting procedures makes it adaptable to various settings, including industrial facilities, urban areas, and remote locations. Overall, our autonomous rover system represents a substantial advancement in firefighting technology, offering swift and efficient fire detection and extinguishing capabilities to mitigate fire hazards effectively. Keywords— NodeMCU, Rover, Flame Sensors, Servomotor, L293d motor drivers, Li-ion batteries

LunarSim: Lunar Rover Simulator Focused on High Visual Fidelity and ROS 2 Integration for Advanced Computer Vision Algorithm Development

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.

Research on the Driving Simulation Method of a Manned Lunar Rover System for Somatosensory Representation

Research on the Driving Simulation Method of a Manned Lunar Rover System for Somatosensory Representation

A methodology for developing SoS architectures using SysML model federation

AbstractAn essential role of systems engineering is to aid in overcoming complexity during development. As system complexity increases, a greater number of organizations are being asked to contribute architecture/design content for systems development. An essential challenge to overcome is how to ensure digital continuity in connecting system models to form systems of systems (SoS) models. Leveraging recent developments in digital engineering (DE) and model‐based systems engineering (MBSE) this paper presents a SysML model federation methodology enabling multiple collaborating organizations to contribute system models and form a descriptive SoS architecture model. Systems engineers applying this methodology are able to reuse constituent system model content to describe the larger SoS behavior and structure while promoting reusability and commonality and are therefore better able to ensure correctness and consistency across development. First, a background through the review of SoS engineering (SoSE) and DE/MBSE literature is provided. Then an MBSE process along with specific methods tailoring the use of SysML within the Cameo Enterprise Architecture tool is presented. This work builds upon a previously published Systems Architecture Model (SAM) development method and is designed to permit style diversity across peer constituent models and ensure that every piece of data has an authoritative source of truth (ASOT) within the federation. This paper then presents the application of this methodology to the Ranger Lunar Rover system by making use of its openly published SysML model. Finally, the benefits and challenges of this methodology are discussed prior to drawing closing conclusions and identifying future areas of research.

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.

A computational tool for conceptual design and optimization of planetary rovers

The design process of a Mars rover is driven by multiple design constraints, namely overall mass, power consumption and volume (dimensions). Various systems, such as mobility, manipulation, handling, power, thermal, communication, navigation, avionics and science instruments, together make a complete rover vehicle and they should function collectively to perform a given task. Each of the subsystems can be thought of as modular building blocks that are integrated together to form a fully functional rover vehicle. When approaching the design of such a vehicle, the designer should take into account of cross design dependencies existent between different subsystems and technology limitations. Performing any particular task, would lead to many design possibilities. Choosing the final design from many feasible solutions is arguably a daunting task. In order to make this process simple and convenient, as well as to understand the design non-linearity existing in this solution space, the authors have employed a systems engineering approach to develop a tool comprising subsystem models. The subsystem models comprise parametric and physics-based models. For designing suitable user-defined objectives, these models when integrated with Genetic Algorithm forms an effective tool to support design trade-offs during the conceptual design process. This integrated modeling and optimization approach is thought to be efficient in identifying rover system concepts.

Strawberry localization in a ridge planting with an autonomous rover

Having complete knowledge of a strawberry crop field is helpful in making crucial decisions and optimizing strawberry production. For that aim, autonomous robots have played a crucial role in getting such information through various sensors in the last few years. In this context, we present an autonomous rover system that detects strawberries and estimates their ripeness in a natural crop field through visual information using a stereo camera. With that aim, we propose an algorithm that uses image processing techniques with deep learning approaches. Furthermore, we construct a strawberry map to provide the farmer with information regarding the growing state of the fruit, health, and even a production estimation. Moreover, the rover and the vision algorithm are designed to work on ridge planting, a kind of strawberry crop field where uneven terrains, narrow spaces, and rugged backgrounds are presented. Experiments were conducted in a natural crop field, showing satisfactory results; from comparison results with the most recent work in the state-of-the-art, we observe that our system detects 14% more strawberries. Furthermore, a video showing the obtained results is presented. Finally, intending to contribute to the community, we release the code corresponding to our proposed method on our GitHub website.

Heterogeneous computing for low-cost robotic platforms

This study presents a novel approach to the design of cost-effective autonomous rovers using a heterogeneous computing architecture. The research focuses on the development and evaluation of an autonomous rover system, priced under $2 700 (USD), that can operate independently in various environments. The system’s performance was assessed in real-world conditions, demonstrating an average speed of 0.5 m/s, an energy consumption of 0.2 kWh, and a decision-making error rate below 5%. The results suggest that the use of heterogeneous computing architectures can lead to the development of affordable and efficient autonomous navigation systems. The paper concludes by discussing potential future research directions and the broader implications of these findings for the field of autonomous systems.

SegMarsViT: Lightweight Mars Terrain Segmentation Network for Autonomous Driving in Planetary Exploration

Planetary rover systems need to perform terrain segmentation to identify feasible driving areas and surround obstacles, which falls into the research area of semantic segmentation. Recently, deep learning (DL)-based methods were proposed and achieved great performance for semantic segmentation. However, due to the on-board processor platform’s strict comstraints on computational complexity and power consumption, existing DL approaches are almost impossible to be deployed on satellites under the burden of extensive computation and large model size. To fill this gap, this paper targeted studying effective and efficient Martian terrain segmentation solutions that are suitable for on-board satellites. In this article, we propose a lightweight ViT-based terrain segmentation method, namely, SegMarsViT. In the encoder part, the mobile vision transformer (MViT) block in the backbone extracts local–global spatial and captures multiscale contextual information concurrently. In the decoder part, the cross-scale feature fusion modules (CFF) further integrate hierarchical context information and the compact feature aggregation module (CFA) combines multi-level feature representation. Moreover, we evaluate the proposed method on three public datasets: AI4Mars, MSL-Seg, and S5Mars. Extensive experiments demonstrate that the proposed SegMarsViT was able to achieve 68.4%, 78.22%, and 67.28% mIoU on the AI4Mars-MSL, MSL-Seg, and S5Mars, respectively, under the speed of 69.52 FPS.

Precise pose estimation of the NASA Mars 2020 Perseverance rover through a stereo‐vision‐based approach

AbstractVisual Odometry (VO) is a fundamental technique to enhance the navigation capabilities of planetary exploration rovers. By processing the images acquired during the motion, VO methods provide estimates of the relative position and attitude between navigation steps with the detection and tracking of two‐dimensional (2D) image keypoints. This method allows one to mitigate trajectory inconsistencies associated with slippage conditions resulting from dead‐reckoning techniques. We present here an independent analysis of the high‐resolution stereo images of the NASA Mars 2020 Perseverance rover to retrieve its accurate localization on sols 65, 66, 72, and 120. The stereo pairs are processed by using a 3D‐to‐3D stereo‐VO approach that is based on consolidated techniques and accounts for the main nonlinear optical effects characterizing real cameras. The algorithm is first validated through the analysis of rectified stereo images acquired by the NASA Mars Exploration Rover Opportunity, and then applied to the determination of Perseverance's path. The results suggest that our reconstructed path is consistent with the telemetered trajectory, which was directly retrieved onboard the rover's system. The estimated pose is in full agreement with the archived rover's position and attitude after short navigation steps. Significant differences (~10–30 cm) between our reconstructed and telemetered trajectories are observed when Perseverance traveled distances larger than 1 m between the acquisition of stereo pairs.

In situ Lu–Hf phosphate geochronology: Progress towards a new tool for space exploration

Geochronology is fundamental to understanding planetary evolution. However, as space exploration continues to expand, traditional dating methods, involving complex laboratory processes, are generally not realistic for unmanned space applications. Campaign-style planetary exploration missions require dating methods that can (1) rapidly resolve age information on small samples, (2) be applied to minerals common in mafic rocks, and (3) be based on technologies that could be installed on future rover systems. We demonstrate the application of rapid in situ microanalytical Lu–Hf phosphate geochronology using samples of pallasite meteorites, which are representative examples of the deep interiors of differentiated planetoids that are generally difficult to date. Individual pallasites were dated by laser ablation tandem mass-spectrometry (LA-ICP-MS/MS), demonstrating a rapid novel method for exploring planetary evolution. Derived formation ages for individual pallasites agree with traditional methods and have <2% uncertainty, opening an avenue of opportunity for remote micro-analytical space exploration.

Marimo actuated rover systems

BackgroundThe potential to directly harness photosynthesis to make actuators, biosensors and bioprocessors has been previously demonstrated in the literature. Herein, this capability has been expanded to more advanced systems — Marimo Actuated Rover Systems (MARS) — which are capable of autonomous, solar powered, movement.ResultsWe demonstrate this ability is both a practical and viable alternative to conventional mobile platforms for exploration and dynamic environmental monitoring. Prototypes have been successfully tested to measure their speed of travel and ability to automatically bypass obstacles. Further, MARS is electromagnetically silent, thus avoiding the background noise generated by conventional electro/mechanical platforms which reduces instrument sensitivity. The cost of MARS is significantly lower than platforms based on conventional technology.ConclusionsAn autonomous, low-cost, lightweight, compact size, photosynthetically powered rover is reported. The potential for further system enhancements are identified and under development.

Multi-disciplinary and Multi-objective Design Optimization of a Lunar Rover System with Operational Considerations

Multi-disciplinary and Multi-objective Design Optimization of a Lunar Rover System with Operational Considerations

Using Additional Moderator to Control the Footprint of a COSMOS Rover for Soil Moisture Measurement

AbstractCosmic‐Ray Neutron Probes (CRNP) have found application in soil moisture (SM) estimation due to their conveniently large (&gt;100 m) footprints. Here, we explore the possibility of using high‐density polyethylene (HDPE) moderator to limit the field of view, and hence, the footprint of a SM sensor formed of 12 CRNP mounted on to a mobile robotic platform (Thorvald) for better in‐field localization of moisture variation. Ultra Rapid Adaptable Neutron‐Only Simulation neutron scattering simulations are used to show that 5 cm of additional HDPE moderator (used to shield the upper surface and sides of the detector) is sufficient to (a) reduce the footprint of the detector considerably, (b) approximately double the percentage of neutrons detected from within 5 m of the detector, and (c) does not affect the shape of the curve used to convert neutron counts into SM. Simulation and rover measurements for a transect crossing between grass and concrete additionally suggest that (d) SM changes can be sensed over a length scales of tens of meters or less (roughly an order of magnitude smaller than commonly used footprint distances), and (e) the additional moderator does not reduce the detected neutron count rate (and hence increase noise) as much as might be expected given the extent of the additional moderator. The detector with additional HDPE moderator was also used to conduct measurements on a stubble field over three weeks to test the rover system in measuring spatial and temporal SM variation.

Learning-Based End-to-End Path Planning for Lunar Rovers with Safety Constraints.

Path planning is an essential technology for lunar rover to achieve safe and efficient autonomous exploration mission, this paper proposes a learning-based end-to-end path planning algorithm for lunar rovers with safety constraints. Firstly, a training environment integrating real lunar surface terrain data was built using the Gazebo simulation environment and a lunar rover simulator was created in it to simulate the real lunar surface environment and the lunar rover system. Then an end-to-end path planning algorithm based on deep reinforcement learning method is designed, including state space, action space, network structure, reward function considering slip behavior, and training method based on proximal policy optimization. In addition, to improve the generalization ability to different lunar surface topography and different scale environments, a variety of training scenarios were set up to train the network model using the idea of curriculum learning. The simulation results show that the proposed planning algorithm can successfully achieve the end-to-end path planning of the lunar rover, and the path generated by the proposed algorithm has a higher safety guarantee compared with the classical path planning algorithm.

Estimation and Mapping of System-Surface Interaction by Combining Nonlinear Optimization and Machine Learning

Abstract Exploring unknown environments is one of the main applications of mobile robotic systems. Since explorative trajectories can be used to gather information on the environment as well as on the internal dynamics of the robotic system, we propose a combined parameter estimation and mapping approach consisting of three steps: first, the parameter estimation problem is addressed by nonlinear optimization. Then, clustering is used to classify the estimated parameters. Finally, Support Vector Machines (SVMs) are used to expand the optimal parameter values of the recorded data onto the entire map. The proposed approach is applied to a wheeled mobile rover system in a scenario with sharply changing surface properties. Further, it is assumed that the model structure is known and the slip parameter is estimated during the exploration as it depends on system-surface interaction. From the simulations, it was demonstrated that the proposed approach can estimate the position-dependent slip parameter and identify more than 90% of the surface map.

Potensi Timah Primer Daerah Nyelanding Berdasarkan Analisis Data Geomagnet

The village area of Nyelanding is estimated that there are still many regions that have primary tin prospects, this is confirmed by the large number of community mines that are still operating. This research purposes to see the distribution of primary tin mineralization and zones where deposition of tin. This research uses a geomagnetic exploration survey method with back – rover (mobile) system, the length of the track of ±3.5 km. The spacing of 200 m as many as 44 tracks, the direction of the track from south to north with data collection techniques starting from west to east. The data obtained of a magnetic strength value which will then be interpreted into a magnetic anomaly map to determine the location of recommendations. The research method used the Geomagnetic Survey method, of GSM-19 T Magnetometer. The interpretation results, the final map with the lowest magnetic anomaly shows magnetic anomaly values ranging from -7.2 to -3.3 nT at locations 1, 2, 3, the highest magnetic anomaly ranges from -4.6 to 5.0 nT in the southern part which is an area close to community settlements and the village highway of Nyelanding, and the direction of mineral distribution for zone 1 starts from east-west, zone 2 focuses towards the middle which means from southwest-northeast direction or vice versa, zone 3 from southwest-northeast. The upward continuity map 250 and matching the location of samples containing Sn levels around the recommended zone, it is certain that the area has cassiterite minerals in the zone namely zone 1 = (342.760 m2), zone 2 = (4001.770 m2), zone 3 = (372.876 m2).

The Application of Low-Cost, Close-Range Photogrammetry in Dentistry

The search for extant life has long been an interest since people have been able to successfully explore other worlds. However, on space missions, experiments must be performed autonomously, with limited resources, and a carefully selected suite of instruments. Instruments are additionally constrained by weight, reliability, and size which limits use of many modern advanced systems. The Queen’s Space Engineering Team (QSET) is proposing the design of a portable (12” x 12” x 12”) instrument to identify signs supporting extant life aboard a mobile rover platform during exploration missions. The instrument will receive soil samples collected by the rover, analyse the composition to identify key molecules, and transmit data back to a ground station. This system relies on colorimetric measurements using a UV-VIS spectrometer and features a solvent recycle system to minimize weight and waste. This project is part of a larger environment characterisation module to be mounted on a Mars rover system designed for competition at the University Rover Challenge (URC) at the Mars Desert Research Station (MDRS) in Utah. As of this date, each subsystem has successfully passed performance testing and the entire instrument is entering its system-level prototyping stage.

Enabling new exploration opportunities on planetary surfaces: In situ geochemical characterization in soils by dielectric spectroscopy onboard the AXEL rover system

In the work, we present dielectric spectroscopy (DS) is an analytical method capable of characterizing and quantifying electrochemically active materials (water/ice, ions, etc.) in planetary regoliths. Detection of these materials occurs when a small amount of energy is applied to an in situ sample, causing perturbation in the form of potential kinetic energy and inducing polarization and/or relaxation processes in materials of interest. The frequency dispersion on the electrical properties of impendences, relative permittivity, and conductivity spectra represents chemical and physical properties in association with inherent material properties. Therefore, measuring these energetic states can provide a unique fingerprint of the materials, depending on the frequencies that are scanned. In the case of water content in soils, the Debye equivalent circuit model can accurately predict its electrical properties and provide excellent quantification of the water content in soils.Use of DS is enabled by miniaturization of the key components and the low power requirements. DS is therefore capable of offering substantial scientific returns as an in situ sampling and non-destructive measurement technique, making it ideally suitable for deployment onboard many smaller space exploratory platforms. This work reports the first deployment use of DS from a field test for geochemical characterization of in situ soils, specifically on the quantification of water onboard the AXEL mobility system in the Mojave Desert.Laboratory testing has confirmed the sensitivity of DS with respect to particle size (fine vs coarse) determination as well as water content (down to 0.01 ​wt%) under a wide range of environmental conditions. Water content associated with bound and bulk water was uniquely identified in the soil mixture. We also describe a field demonstration using DS using two distinct insertion dielectric probes specifically design for sub-surface measurements, verifying their mechanical robustness and chemical stability. The field measurements are in good agreement with laboratory data and effectively quantified water content at about 3.0 ​wt% and 8.0 ​wt% for field test sites #1 and #2, respectively.

Enabling outdoor MR capabilities for head mounted displays: a case study

This research work covers generic approaches to determine the outdoor position and orientation of an augmented reality device due to the lack of outdoor capability of depth-sensor or environmental recognition-sensor-based devices currently available on the market. The determination of the orientation is primarily achieved with an attitude heading reference system (AHRS) for a rough estimation. Based on a connected/built-in video camera the accuracy at minor changes of the orientation is enhanced by applying registration to assess the differences in orientation between two video frames, compensating for gyroscope drift errors. The position determination is achieved using GPS with a rover and base station real time kinematic beacon system to achieve enhanced precision. Results show that due to sensor application AR hardware considered for indoor use can be retooled to properly work outdoors, at large distances and even inside running vehicles. Thus, future implementation of applications in various domains is facilitated.