Path planning, modelling and simulation for energy optimised mobile robotics

This thesis is concerned with an investigation of a solution for mobile robotic platforms to minimize the usage of scarce energy that is available and is not wasted following traditionally planned paths for complex terrain environments. This therefore addresses the need to reduce the total energy cost during a field task or mission. A path planning algorithm is designed by creating a new approach of artificial potential field method that generates a planned path, utilising terrain map. The new approach has the capability of avoiding the local minimum problems which is one of the major problems of traditional potential field method. By solving such problems gives a reliable solution to establish a required path. Therefore the approach results in an energy efficient path of the terrain identified, instead obvious straight line of the terrain. A literature review is conducted which reviews the mainstream path planning algorithms with the applications in mobile robotic platforms was analysed. These path planning algorithms are compared for the purpose of energy optimized planning, which concludes the method of artificial potential field as the path planning algorithm which has the most potential and will be further investigated and improved in this research. The methodology of designing, modelling and simulating a mobile robotic platform is defined and presented for the purpose of energy optimized path planning requirement. The research is to clarify the needs, requirements, and specifications of the design. A complete set of models which include mechanical and electrical modelling, functional concept modelling, modelling of the system are established. Based on these models, an energy optimized path planning algorithm is designed. The modelling of force and the kinematics is established to validate and evaluate the result of the algorithm through simulations. Moreover a simulation environment is established which is constructed for multi perspective simulation. This also enables collaborative simulation using Simulink and ADAMS to for simulating a path generated by the path planning algorithm and assess the energy consumption of the driven and steering mechanism of an exemplar system called AgriRover. This simulation environment allows the capture of simulated result of the total energy consumption, therefore outlines the energy cost behaviour of the AgriRover. A total of two sets of paths was tested in the fields for validation, one being generated by the energy optimized path planning algorithm and the other following a straight path. During the field tests the total cost of energy was captured . Two sets of results are compared with each other and compared with the simulation. The comparison shows a 21.34% of the energy saving by deploying the path generated with the energy optimized path planning algorithm in the field test. This research made the following contribution to knowledge. A comparison and grading of mainstream path planning algorithms from energy optimisation perspective is undertaken using detailed evaluation criteria, including computational power required, extendibility, flexibility and more criteria that is relevant for the energy optimized planning purpose. These algorithms have not been compared from energy optimisation angle before, and the research for energy optimised planning under complex terrain environments have not been investigated. Addressing these knowledge gaps, a methodology of designing, modelling and simulating a mobile platform system is proposed to facilitate an energy optimized path planning. This , leads to a new approach of path planning algorithm that reduces unnecessary energy spend for climbing of the terrain, using the terrain data available. Such a methodology derives several novel methods: Namely, a method for avoiding local minimum problem for artificial potential field path planning using the approach of approximation; A method of achieving high expendability of the path planning algorithm, where this method is capable of generate a path through a large map in a short time; A novel method of multi perspective dynamic simulation, which is capable of simulating the behaviour of internal mechanism and the overall robotic mobile platform with the fully integrated control, The dynamic simulation enables prediction of energy consumption; Finally, a novel method of mathematically modelling and simplifying a steering mechanism for the wheel based mobile vehicle was further investigated.This thesis is concerned with an investigation of a solution for mobile robotic platforms to minimize the usage of scarce energy that is available and is not wasted following traditionally planned paths for complex terrain environments. This therefore addresses the need to reduce the total energy cost during a field task or mission. A path planning algorithm is designed by creating a new approach of artificial potential field method that generates a planned path, utilising terrain map. The new approach has the capability of avoiding the local minimum problems which is one of the major problems of traditional potential field method. By solving such problems gives a reliable solution to establish a required path. Therefore the approach results in an energy efficient path of the terrain identified, instead obvious straight line of the terrain. A literature review is conducted which reviews the mainstream path planning algorithms with the applications in mobile robotic platforms was analysed. These path planning algorithms are compared for the purpose of energy optimized planning, which concludes the method of artificial potential field as the path planning algorithm which has the most potential and will be further investigated and improved in this research. The methodology of designing, modelling and simulating a mobile robotic platform is defined and presented for the purpose of energy optimized path planning requirement. The research is to clarify the needs, requirements, and specifications of the design. A complete set of models which include mechanical and electrical modelling, functional concept modelling, modelling of the system are established. Based on these models, an energy optimized path planning algorithm is designed. The modelling of force and the kinematics is established to validate and evaluate the result of the algorithm through simulations. Moreover a simulation environment is established which is constructed for multi perspective simulation. This also enables collaborative simulation using Simulink and ADAMS to for simulating a path generated by the path planning algorithm and assess the energy consumption of the driven and steering mechanism of an exemplar system called AgriRover. This simulation environment allows the capture of simulated result of the total energy consumption, therefore outlines the energy cost behaviour of the AgriRover. A total of two sets of paths was tested in the fields for validation, one being generated by the energy optimized path planning algorithm and the other following a straight path. During the field tests the total cost of energy was captured . Two sets of results are compared with each other and compared with the simulation. The comparison shows a 21.34% of the energy saving by deploying the path generated with the energy optimized path planning algorithm in the field test. This research made the following contribution to knowledge. A comparison and grading of mainstream path planning algorithms from energy optimisation perspective is undertaken using detailed evaluation criteria, including computational power required, extendibility, flexibility and more criteria that is relevant for the energy optimized planning purpose. These algorithms have not been compared from energy optimisation angle before, and the research for energy optimised planning under complex terrain environments have not been investigated. Addressing these knowledge gaps, a methodology of designing, modelling and simulating a mobile platform system is proposed to facilitate an energy optimized path planning. This , leads to a new approach of path planning algorithm that reduces unnecessary energy spend for climbing of the terrain, using the terrain data available. Such a methodology derives several novel methods: Namely, a method for avoiding local minimum problem for artificial potential field path planning using the approach of approximation; A method of achieving high expendability of the path planning algorithm, where this method is capable of generate a path through a large map in a short time; A novel method of multi perspective dynamic simulation, which is capable of simulating the behaviour of internal mechanism and the overall robotic mobile platform with the fully integrated control, The dynamic simulation enables prediction of energy consumption; Finally, a novel method of mathematically modelling and simplifying a steering mechanism for the wheel based mobile vehicle was further investigated

SSERVI Annual Report: Year 4

The SSERVI Central Office forms the organizational, administrative and collaborative hub for the domestic and international teams, and is responsible for advocacy and ensuring the long-term health and relevance of the Institute. SSERVI has increased the cross-talk between NASAs space and human exploration programs, which is one of our primary goals. We bring multidisciplinary teams together to address fundamental and strategic questions pertinent to future human space exploration, and the results from that research are the primary products of the institute. The team and international partnership reports contain summaries of 2017 research accomplishments. Here we present the 2017 accomplishments by the SSERVI Central Office that focus on: 1) Supporting Our Teams, 2) Community Building, 3) Managing the Solar System Treks Portal (SSTP), and 4) Public Engagement

Artificial Intelligence for Small Satellites Mission Autonomy

Space mission engineering has always been recognized as a very challenging and innovative branch of engineering: since the beginning of the space race, numerous milestones, key successes and failures, improvements, and connections with other engineering domains have been reached. Despite its relative young age, space engineering discipline has not gone through homogeneous times: alternation of leading nations, shifts in public and private interests, allocations of resources to different domains and goals are all examples of an intrinsic dynamism that characterized this discipline. The dynamism is even more striking in the last two decades, in which several factors contributed to the fervour of this period. Two of the most important ones were certainly the increased presence and push of the commercial and private sector and the overall intent of reducing the size of the spacecraft while maintaining comparable level of performances. A key example of the second driver is the introduction, in 1999, of a new category of space systems called CubeSats. Envisioned and designed to ease the access to space for universities, by standardizing the development of the spacecraft and by ensuring high probabilities of acceptance as piggyback customers in launches, the standard was quickly adopted not only by universities, but also by agencies and private companies. CubeSats turned out to be a disruptive innovation, and the space mission ecosystem was deeply changed by this. New mission concepts and architectures are being developed: CubeSats are now considered as secondary payloads of bigger missions, constellations are being deployed in Low Earth Orbit to perform observation missions to a performance level considered to be only achievable by traditional, fully-sized spacecraft. CubeSats, and more in general the small satellites technology, had to overcome important challenges in the last few years that were constraining and reducing the diffusion and adoption potential of smaller spacecraft for scientific and technology demonstration missions. Among these challenges were: the miniaturization of propulsion technologies, to enable concepts such as Rendezvous and Docking, or interplanetary missions; the improvement of telecommunication state of the art for small satellites, to enable the downlink to Earth of all the data acquired during the mission; and the miniaturization of scientific instruments, to be able to exploit CubeSats in more meaningful, scientific, ways. With the size reduction and with the consolidation of the technology, many aspects of a space mission are reduced in consequence: among these, costs, development and launch times can be cited. An important aspect that has not been demonstrated to scale accordingly is operations: even for small satellite missions, human operators and performant ground control centres are needed. In addition, with the possibility of having constellations or interplanetary distributed missions, a redesign of how operations are management is required, to cope with the innovation in space mission architectures. The present work has been carried out to address the issue of operations for small satellite missions. The thesis presents a research, carried out in several institutions (Politecnico di Torino, MIT, NASA JPL), aimed at improving the autonomy level of space missions, and in particular of small satellites. The key technology exploited in the research is Artificial Intelligence, a computer science branch that has gained extreme interest in research disciplines such as medicine, security, image recognition and language processing, and is currently making its way in space engineering as well. The thesis focuses on three topics, and three related applications have been developed and are here presented: autonomous operations by means of event detection algorithms, intelligent failure detection on small satellite actuator systems, and decision-making support thanks to intelligent tradespace exploration during the preliminary design of space missions. The Artificial Intelligent technologies explored are: Machine Learning, and in particular Neural Networks; Knowledge-based Systems, and in particular Fuzzy Logics; Evolutionary Algorithms, and in particular Genetic Algorithms. The thesis covers the domain (small satellites), the technology (Artificial Intelligence), the focus (mission autonomy) and presents three case studies, that demonstrate the feasibility of employing Artificial Intelligence to enhance how missions are currently operated and designed

Proceedings Of The 18th Annual Meeting Of The Asia Oceania Geosciences Society (Aogs 2021)

The 18th Annual Meeting of the Asia Oceania Geosciences Society (AOGS 2021) was held from 1st to 6th August 2021. This proceedings volume includes selected extended abstracts from a challenging array of presentations at this conference. The AOGS Annual Meeting is a leading venue for professional interaction among researchers and practitioners, covering diverse disciplines of geosciences

Concepts and Approaches for Mars Exploration

Abstracts describe missions, mission elements or experiments for consideration in the 2005-2020 time frame. Also the technologies and the support necessary to achieve the results are discussed.NASA Headquarters; Lunar and Planetary Institutehosted by Lunar and Planetary Institute ; sponsored by NASA Headquarters, Lunar and Planetary Institute ; convener Scott Hubbard

Deep Space Gateway Concept Science Workshop : February 27–March 1, 2018, Denver, Colorado

The purpose of this workshop is to discuss what science could be leveraged from a deep space gateway, as well as first-order determination of what instruments are required to acquire the scientific data.Institutional Support, National Aeronautics and Space Administration, Lunar and Planetary Institute, Universities Space Research Association ; Executive Committee, Ben Bussey, HEOMD Chief Scientist, NASA Headquarters, Jim Garvin, Goddard Space Flight Center Chief Scientist, Michael New, NASA Headquarters, Deputy AA for Research, SMD, Paul Niles, Executive Secretary, NASA Johnson Space Center, Jim Spann, MSFC Chief Scientist, Eileen Stansbery, Johnson Space CenterPARTIAL CONTENTS: Deep Space Gateway as a Deployment Staging Platform and Communication Hub of Lunar Heat Flow Experiment--Lunar Seismology Enabled by a Deep Space Gateway--In-Situ Measurements of Electrostatic Dust Transport on the Lunar Surface--Science Investigations Enabled by Magnetic Field Measurements on the Lunar Surface--Enhancing Return from Lunar Surface Missions via the Deep Space Gateway--Deep Space Gateway Support of Lunar Surface Ops and Tele-Operational Transfer of Surface Assets to the Next Landing Site--Development of a Lunar Surface Architecture Using the Deep Space Gateway--The Deep Space Gateway: The Next Stepping Stone to Mar

Algorithms for multi-robot systems on the cooperative exploration & last-mile delivery problems

La aparición de los vehículos aéreos no tripulados (UAVs) y de los vehículos terrestres no tripulados (UGVs) ha llevado a la comunidad científica a enfrentarse a problemas ideando paradigmas de cooperación con UGVs y UAVs. Sin embargo, no suele ser trivial determinar si la cooperación entre UGVs y UAVs es adecuada para un determinado problema. Por esta razón, en esta tesis, investigamos un paradigma particular de cooperación UGV-UAV en dos problemas de la literatura, y proponemos un controlador autónomo para probarlo en escenarios simulados. Primero, formulamos un problema particular de exploración cooperativa que consiste en alcanzar un conjunto de puntos de destino en un área de exploración a gran escala. Este problema define al UGV como una estación de carga móvil para transportar el UAV a través de diferentes lugares desde donde el UAV puede alcanzar los puntos de destino. Por consiguiente, proponemos el algoritmo TERRA para resolverlo. Este algoritmo se destaca por dividir el problema de exploración en cinco subproblemas, en los que cada subproblema se resuelve en una etapa particular del algoritmo. Debido a la explosión de la entrega de paquetes en las empresas de comercio electrónico, formulamos también una generalización del conocido problema de la entrega en la última milla. En este caso, el UGV actúa como una estación de carga móvil que transporta a los paquetes y a los UAVs, y estos se encargan de entregarlos. De esta manera, seguimos la estrategia de división descrita por TERRA, y proponemos el algoritmo COURIER. Este algoritmo replica las cuatro primeras etapas de TERRA, pero construye una nueva quinta etapa para producir un plan de tareas que resuelva el problema. Para evaluar el paradigma de cooperación UGV-UAV en escenarios simulados, proponemos el controlador autónomo ARIES. Este controlador sigue un enfoque jerárquico descentralizado de líder-seguidor para integrar cualquier paradigma de cooperación de manera distribuida. Ambos algoritmos han sido caracterizados para identificar los aspectos relevantes del paradigma de cooperación en los problemas relacionados. Además, ambos demuestran un gran rendimiento del paradigma de cooperación en tales problemas, y al igual que el controlador autónomo, revelan un gran potencial para futuras aplicaciones reales.The emergence of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has conducted the research community to face historical complex problems by devising UGV-UAV cooperation paradigms. However, it is usually not a trivial task to determine whether or not a UGV-UAV cooperation is suitable for a particular problem. For this reason, in this thesis, we investigate a particular UGV-UAV cooperation paradigm over two problems in the literature, and we propose an autonomous controller to test it on simulated scenarios. Driven by the planetary exploration, we formulate a particular cooperative exploration problem consisting of reaching a set of target points in a large-scale exploration area. This problem defines the UGV as a moving charging station to carry the UAV through different locations from where the UAV can reach the target points. Consequently, we propose the cooperaTive ExploRation Routing Algorithm (TERRA) to solve it. This algorithm stands out for splitting up the exploration problem into five sub-problems, in which each sub-problem is solved in a particular stage of the algorithm. In the same way, driven by the explosion of parcels delivery in e-commerce companies, we formulate a generalization of the well-known last-mile delivery problem. This generalization defines the same UGV’s and UAV’s rol as the exploration problem. That is, the UGV acts as a moving charging station which carries the parcels along several UAVs to deliver them. In this way, we follow the split strategy depicted by TERRA to propose the COoperative Unmanned deliveRIEs planning algoRithm (COURIER). This algorithm replicates the first four TERRA’s stages, but it builds a new fifth stage to produce a task plan solving the problem. In order to evaluate the UGV-UAV cooperation paradigm on simulated scenarios, we propose the Autonomous coopeRatIve Execution System (ARIES). This controller follows a hierarchical decentralized leader-follower approach to integrate any cooperation paradigm in a distributed manner. Both algorithms have been characterized to identify the relevant aspects of the cooperation paradigm in the related problems. Also, both of them demonstrate a great performance of the cooperation paradigm in such problems, and as well as the autonomous controller, reveal a great potential for future real applications

Proceedings of the 8th Annual Summer Conference: NASA/USRA Advanced Design Program

Papers presented at the 8th Annual Summer Conference are categorized as Space Projects and Aeronautics projects. Topics covered include: Systematic Propulsion Optimization Tools (SPOT), Assured Crew Return Vehicle Post Landing Configuration Design and Test, Autonomous Support for Microorganism Research in Space, Bioregenerative System Components for Microgravity, The Extended Mission Rover (EMR), Planetary Surface Exploration MESUR/Autonomous Lunar Rover, Automation of Closed Environments in Space for Human Comfort and Safety, Walking Robot Design, Extraterrestrial Surface Propulsion Systems, The Design of Four Hypersonic Reconnaissance Aircraft, Design of a Refueling Tanker Delivering Liquid Hydrogen, The Design of a Long-Range Megatransport Aircraft, and Solar Powered Multipurpose Remotely Powered Aircraft

Life as-we-don’t-know-it: research repertoires and the emergence of astrobiology

This thesis presents an ethnographic study of the repertoires, sets of social and material practices, that scientists adopt to practice and promote the search for life in the universe, commonly known today under the disciplinary label of astrobiology. In particular, I take the expression “life as-we-don’t-know-it” as an entry point to look into the role of non-knowledge as a cultural resource in the opening of new spheres of inquiry. Throughout this thesis, I investigate the tensions and negotiations related to the definition of life, a central issue in astrobiology, and the way scientists are successfully shifting the boundaries of what is considered legitimate science to include the study of extra-terrestrial lifeforms. Unlike most previous work on the definition of life, this thesis does not formulate or support any definition and does not take a position on the question of to which disciplinary domain “life” legitimately belongs – on the contrary, it takes definitions and disciplines as social institutions with flexible boundaries. To explore these issues, I engaged in a multi-sited ethnographic study that brought me to the different locations in which astrobiologists’ activities take place, from conference venues to astronomical observatories, laboratories and field sites (such as underground caves and Icelandic volcanoes), following the lines of research that today form, at their intersections, the field of astrobiology. Life “as-we-don’t-know-it” soon emerged as a central theme in contemporary astrobiology. A commonly used phrase for extra-terrestrial and alien life, it summarizes and stands for the uncertainties and unknowns surrounding the definition of life and the design of life-detection experiments. These unknowns about life are not simply a void to be filled, but the result of a process of social construction, a collective achievement. This empirical account complements and challenges existing literature about scientific change and knowledge production by focusing on the construction of a collective agreement about not-knowing and its deployment as a specific research repertoire. The concept of repertoire is a useful thinking tool for the sociologist looking into astrobiology and its social dynamics because it does not describe change as fundamentally caused and shaped by theoretical developments. On the contrary, it both takes account of the material and institutional changes that accompany, ground or undermine the emergence of a research field and calls for consideration of the performative aspects of science. I conclude by arguing that the agreement on what constitutes life – familiar and alien, Earthly or otherworldly – is an ongoing negotiation between astrobiologists’ epistemic practices and what counts as a meaningful present and future for space exploration. This opens up a space for sociological inquiry about the particular social processes through which the emergence of astrobiology as a discipline requires collaborations to be established, allows for new interactions, and evokes previously unforeseen associations, thus constantly unsettling present imaginaries about the future

Planetary Science Vision 2050 Workshop : February 27–28 and March 1, 2017, Washington, DC

This workshop is meant to provide NASA’s Planetary Science Division with a very long-range vision of what planetary science may look like in the future.Organizer, Lunar and Planetary Institute ; Conveners, James Green, NASA Planetary Science Division, Doris Daou, NASA Planetary Science Division ; Science Organizing Committee, Stephen Mackwell, Universities Space Research Association [and 14 others]PARTIAL CONTENTS: Exploration Missions to the Kuiper Belt and Oort Cloud--Future Mercury Exploration: Unique Science Opportunities from Our Solar System’s Innermost Planet--A Vision for Ice Giant Exploration--BAOBAB (Big and Outrageously Bold Asteroid Belt) Project--Asteroid Studies: A 35-Year Forecast--Sampling the Solar System: The Next Level of Understanding--A Ground Truth-Based Approach to Future Solar System Origins Research--Isotope Geochemistry for Comparative Planetology of Exoplanets--The Moon as a Laboratory for Biological Contamination Research--“Be Careful What You Wish For:” The Scientific, Practical, and Cultural Implications of Discovering Life in Our Solar System--The Importance of Particle Induced X-Ray Emission (PIXE) Analysis and Imaging to the Search for Life on the Ocean Worlds--Follow the (Outer Solar System) Water: Program Options to Explore Ocean Worlds--Analogies Among Current and Future Life Detection Missions and the Pharmaceutical/ Biomedical Industries--On Neuromorphic Architectures for Efficient, Robust, and Adaptable Autonomy in Life Detection and Other Deep Space Missions