NAVIGATION, GUIDANCE AND CONTROL FOR PLANETARY LANDING

This dissertation aims to develop algorithms of guidance and control for propulsive terminal phase planetary landing, including a piloting strategy. The algorithms developed here are based on the Embedded Model Control (EMC) principles. Currently, the planetary entry descent and landing are important issues, landing on Mars and Moon has been scientifically rewarding; successful landed robotic systems on the surface of Mars have been achieved. Projects as Mars Science Laboratory MSL inter alia have achieved a successful landing. These new approaches are focused in delivering large amounts of mass with a low uncertainty and in performing the entry, descent and landing sequence for human exploration. The dissertation is divided in two parts, the first part is focused on Pinpoint landing algorithms, piloting definition and its integration with guidance; some simulations runs are provided. The second part of this research describes the Borea project. It shows the modelling of quadrotor dynamics and kinematics. Its propulsive system is studied and an alternative methodology for the propeller modelling is presented. The embedded model control for quadrotor vehicles is developed. Test of GNC algorithms for planetary landing were studied and simulated. The dissertation is divided in two parts, the first part is focused on Pinpoint landing algorithms, piloting definition and its integration with guidance, some simulations runs are provided. The second part of this research describes the Borea project. shows modelling of quadrotor dynamics and kinematics. Its propulsive system is studied and an alternative methodology for the propeller modelling is presented. The embedded model control for quadrotor vehicles is developed. Test of GNC algorithms for planetary landing were studied and simulated

The Borea project: a quadrotor uav cradle-to-grave design for space gnc prototyping and testing

Unmanned Aerial Vehicles (UAVs) and, more specifically, n-copters have come to prominence in the last decade due to their several applications. Also, in the automatic control research community UAVs have drawn great attention, since their non-linear and under-actuated nature making them suitable for testing a wide range of control architectures and algorithms. In this paper, prominent theoretical aspects, simulations, and experimental results of the Borea project are presented. The Borea project aims at testing space guidance, navigation, and control (GNC) algorithms leveraging a simplified, rapidly prototypable, low-cost, and easy-to-test quadrotor platform. More precisely, one of the main project objectives consists in testing Moon and Mars planetary landing algorithms, thanks to the similitude, in the command authority and the landing approach, between n-copters and spacecraft; during the propulsive landing phase. Indeed, both n-copters and spacecraft can provide a thrust vector characterized by constant direction and adjustable magnitude. This similitude approach makes it possible to anticipate issues and avoid failures such as those that occurred in the Schiaparelli Mars Lander. To this aim, the complete control unit design, and the UAV plant electro-mechanical prototyping were addressed; so far. Specifically, the control unit was designed within the framework of the Embedded Model Control (EMC) methodology. The EMC design, based on an internal model, also includes the uncertainties as disturbances to be estimated and actively rejected. The Borea UAV has been endowed with a control system leveraging a wide range of automatic control concepts, ranging from modelling, identification, and linear and non-linear control laws, to deal with its position, velocity, and attitude regulation. To sum up, all these results were achieved by means of a properly structured cradle-to-grave design process which, starting from the simultaneous plant modelling and prototyping, ended up with a complete flight tests campaign. Most notably, the testing process involved intensive numerical simulations as well as multi-stage hardware/plant tests and models validation. From the control perspective, the several developed controllers were tuned and tested, via proper simulations and on-purpose flight tests, aiming at validating, from time to time, specific functionalities and control performances. Finally, some results coming from high-fidelity simulations, the hardware and model testing, and in-flight operations are provided to underline the most relevant aspects of the Borea plant and the control unit performance

A Mission Coordinator Approach for a Fleet of UAVs in Urban Scenarios

Abstract The use of Unmanned Aerial Vehicles (UAVs) is now common, but although they have been for various applications, there are still a lot of challenges that need to be overcome. One key issue is related to standardizing the use of these vehicles in urban environments and guaranteeing a minimum risk level for the population. To rise to these challenges, autonomous strategies that optimize and coordinate vehicles in cooperative missions and avoid human operators should be developed. The novelty of this paper is the development of an autonomous urban mission coordinator, which is responsible for the high-level logistics of a fleet of heterogeneous vehicles. A multi-variable weighted algorithm based on a tree optimization method is also proposed

Embedded Model Control calls for disturbance modeling and rejection

Robust control design is mainly devoted to guaranteeing the closed-loop stability of a model-based control law in the presence of parametric uncertainties. The control law is usually a static feedback law which is derived from a (nonlinear) model using different methodologies. From this standpoint, stability can only be guaranteed by introducing some ignorance coefficients and restricting the feedback control effort with respect to the model-based design. Embedded Model Control shows that, the model-based control law must and can be kept intact in the case of uncertainty, if, under certain conditions, the controllable dynamics is complemented by suitable disturbance dynamics capable of real-time encoding the different uncertainties affecting the ‘embedded model', i.e. the model which is both the design source and the core of the control unit. To be real-time updated the disturbance state is driven by an unpredictable input vector, the noise, which can only be estimated from the model error. The uncertainty-based (or plant-based) design concerns the noise estimator, so as to prevent the model error from conveying uncertainty components (parametric, cross-coupling, neglected dynamics) which are command-dependent and thus prone to destabilizing the controlled plant, into the embedded model. Separation of the components in the low and high frequency domain by the noise estimator itself allows stability recovery and guarantee, and the rejection of low frequency uncertainty components. Two simple case studies endowed with simulated and experimental runs will help to understand the key assets of the methodolog

The global distribution and environmental drivers of the soil antibiotic resistome

Background: Little is known about the global distribution and environmental drivers of key microbial functional traits such as antibiotic resistance genes (ARGs). Soils are one of Earth’s largest reservoirs of ARGs, which are integral for soil microbial competition, and have potential implications for plant and human health. Yet, their diversity and global patterns remain poorly described. Here, we analyzed 285 ARGs in soils from 1012 sites across all continents and created the first global atlas with the distributions of topsoil ARGs. Results: We show that ARGs peaked in high latitude cold and boreal forests. Climatic seasonality and mobile genetic elements, associated with the transmission of antibiotic resistance, were also key drivers of their global distribution. Dominant ARGs were mainly related to multidrug resistance genes and efflux pump machineries. We further pinpointed the global hotspots of the diversity and proportions of soil ARGs. Conclusions: Together, our work provides the foundation for a better understanding of the ecology and global distribution of the environmental soil antibiotic resistome.This project received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement 702057 (CLIMIFUN), a Large Research Grant from the British Ecological Society (agreement no. LRA17\1193; MUSGONET), and from the European Research Council (ERC grant agreement no. 647038, BIODESERT). M. D. B. was also supported by a Ramón y Cajal grant (RYC2018-025483-I). M.D-B. also acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 funded by MCIN/AEI/10.13039/501100011033. M.D-B. is also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014-2020 Objetivo temático “01 - Refuerzo de la investigación, el desarrollo tecnológico y la innovación”) associated with the research project P20_00879 (ANDABIOMA). FTM acknowledges support from Generalitat Valenciana (CIDEGENT/2018/041). J. Z. H and H. W. H. are financially supported by Australian Research Council (DP210100332). We also thank the project CTM2015-64728-C2-2-R from the Ministry of Science of Spain. C. A. G. and N. E. acknowledge funding by the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, funded by the German Research Foundation (FZT 118). TG was financially supported by Slovenian Research Agency (P4-0107, J4-3098 and J4-4547)