Effects of sample pretreatment and particle size on the determination of nitrogen in soil by portable LIBS and potential use on robotic-borne remote Martian and agricultural soil analysis systems

Field determination of nitrogen in soil is of interest for both terrestrial and Martian applications. Improved management of soil nitrogen levels on Earth could benefit global food production, whilst the determination of soil nitrogen on Mars is required to assess the planet's future habitability. In this study, a mobile laser induced breakdown spectroscopy (LIBS) system with a 1064 nm Nd:YAG laser delivering 25 mJ per pulse was used to assess the effects of sample pretreatment on the measurement of nitrogen in soil. Although pelletisation was preferred, simply milling the sample to <100 mm particle size – which may be more feasible on a remote rover-based analytical platform – improved the spectra obtained. Ablation craters formed in targets prepared from different particle size fractions of the same commercially-available topsoil showed a clear trend in morphology, with smaller particles yielding more uniform craters with fewer fractures. The LIBS emission intensity at 746.83 nm followed a similar trend to results obtained for total nitrogen content in the soil particle size fractions by microanalysis (Perkin Elmer CHN Elemental Analyser) and was well-correlated (R2 = 0.94) with soil nitrate determined by ion chromatography (Dionex DX-100). Although correlations were less good when analysing field soil samples collected from central Scotland (R2 = 0.82 for comparison between LIBS and microanalysis) the study nevertheless demonstrates the potential of portable LIBS for measurement of soil nitrogen content

Model-Based Systems Engineering in Concurrent Engineering Centers

Concurrent Engineering Centers (CECs) are specialized facilities with a goal of generating and maturing engineering designs by enabling rapid design iterations. This is accomplished by co-locating a team of experts (either physically or virtually) in a room with a focused design goal and a limited timeline of a week or less. The systems engineer uses a model of the system to capture the relevant interfaces and manage the overall architecture. A single model that integrates other design information and modeling allows the entire team to visualize the concurrent activity and identify conflicts more efficiently, potentially resulting in a systems model that will continue to be used throughout the project lifecycle. Performing systems engineering using such a system model is the definition of model-based systems engineering (MBSE); therefore, CECs evolving their approach to incorporate advances in MBSE are more successful in reducing time and cost needed to meet study goals. This paper surveys space mission CECs that are in the middle of this evolution, and the authors share their experiences in order to promote discussion within the community

Model-Based Systems Engineering in Concurrent Engineering Centers

Concurrent Engineering Centers (CECs) are specialized facilities with a goal of generating and maturing engineering designs by enabling rapid design iterations. This is accomplished by co-locating a team of experts (either physically or virtually) in a room with a narrow design goal and a limited timeline of a week or less. The systems engineer uses a model of the system to capture the relevant interfaces and manage the overall architecture. A single model that integrates other design information and modeling allows the entire team to visualize the concurrent activity and identify conflicts more efficiently, potentially resulting in a systems model that will continue to be used throughout the project lifecycle. Performing systems engineering using such a system model is the definition of model-based systems engineering (MBSE); therefore, CECs evolving their approach to incorporate advances in MBSE are more successful in reducing time and cost needed to meet study goals. This paper surveys space mission CECs that are in the middle of this evolution, and the authors share their experiences in order to promote discussion within the community

The Self-Supervised Spectral–Spatial Vision Transformer Network for Accurate Prediction of Wheat Nitrogen Status from UAV Imagery

Nitrogen (N) fertilizer is routinely applied by farmers to increase crop yields. At present, farmers often over-apply N fertilizer in some locations or at certain times because they do not have high-resolution crop N status data. N-use efficiency can be low, with the remaining N lost to the environment, resulting in higher production costs and environmental pollution. Accurate and timely estimation of N status in crops is crucial to improving cropping systems’ economic and environmental sustainability. Destructive approaches based on plant tissue analysis are time consuming and impractical over large fields. Recent advances in remote sensing and deep learning have shown promise in addressing the aforementioned challenges in a non-destructive way. In this work, we propose a novel deep learning framework: a self-supervised spectral–spatial attention-based vision transformer (SSVT). The proposed SSVT introduces a Spectral Attention Block (SAB) and a Spatial Interaction Block (SIB), which allows for simultaneous learning of both spatial and spectral features from UAV digital aerial imagery, for accurate N status prediction in wheat fields. Moreover, the proposed framework introduces local-to-global self-supervised learning to help train the model from unlabelled data. The proposed SSVT has been compared with five state-of-the-art models including: ResNet, RegNet, EfficientNet, EfficientNetV2, and the original vision transformer on both testing and independent datasets. The proposed approach achieved high accuracy (0.96) with good generalizability and reproducibility for wheat N status estimation

The AgriRover : a mechatronic platform from space robotics for precision farming

This paper reports an investigation of a novel development by spinning off space robotic technologies into agriculture and dissemination of the findings of AgriRover project, which is the first of its kind in exploiting and applying space robotic technologies in precision farming. To measure energy performance of mobile platform, a new dynamic total cost of transport is proposed and validated. An autonomous navigation system based on a rover control architecture has been developed to enable the AgriRover to traverse safely in unstructured farming environments. A novel and agriculture- specific object recognition algorithm has been investigated and implemented to enable higher degree of intelligence based on more smart data processing capability. A novel soil sample collecting mechanism has been designed and prototyped for onboard and in-situ soil quality measurement. The design of the whole system has benefited from the use of a mechatronic design process known as the Tiv model through which a planetary rover is reinvented into the AgriRover for agricultural applications. The AgriRover system has gone through three field trials in the UK and China and some of these results are reported

Design concepts and implementation of the Lightweight Advanced Robotic Arm Demonstrator (LARAD)

Beyond the current ExoMars programme, the European Space Agency (ESA) is investigating a range of technology developments and exploration mission opportunities leading to a future Mars Sample Return Mission (MSR), a critical next in the exploration of Mars. To fulfil their scientific objectives, all of these missions require an arm with a long reach capable of performing a variety of tasks in stringent environmental conditions, such as low gravity sampling and precise sample handling and insertion. As part of a CREST-2 project supported by the UK Space Agency (UKSA), a consortium of UK companies have co-founded and developed LARAD, a new Lightweight Advanced Robotic Arm Demonstrator to address some of the underlying challenges related both to the design as well as operation of long arms to perform the payload deployment and sample return operations of future missions. The 15kg terrestrial demonstrator is built as a 2m long arm with 6 degrees of freedom. This arm is capable of deploying a payload with a mass up to 6kgs or operating a 4kg end-effector at 2m. It is using cutting edge technologies on both the hardware and software levels. The mechanical structure of the arm has been manufactured using an array of new processes such as optimised 3D printed titanium Additive Layer Manufactured (ALM) joints, Titanium/Silicon carbide metallic composites, and 3D printed harness routing drums. A modular joint design has been produced, featuring three mechanical sizes of joints each with integrated low level communication and motor drive. The electronics, software and sensors used in the joints are common across all sizes, increasing modularity. To achieve precise positioning, very high resolution absolute position sensing is used on-board. The arm uses novel collision avoidance and path-planning strategies combined with classical control loops. The On-board Control System?s state machine combines different control strategies/modes (i.e. joint trajectory tracking, direct motor control, autonomous placement) depending on the high level user operation requirements. The high level On Board Computer (OBC) is Robot Operating System (ROS) based, enabling a flexible software approach. This project will provide a unique and representative platform to plan and rehearse science operations with full mass payload and instruments, unlike typical planetary arm developments that require scaled-mass end-effector. This paper describes the current state-of-the-art in planetary robotics and provides an overview of the top-level architecture, implementation and laboratory testing phases for the LARAD robotic arm.Peer reviewe