Robot Control Using Inductive, Deductive and Case Based Reasoning

The paper deals with a problem of intelligent system’s design for complex environments. There is discussed a possibility to integrate several technologies into one basic structure that could form a kernel of an autonomous intelligent robotic system. One alternative structure is proposed in order to form a basis of an intelligent system that would be able to operate in complex environments. The proposed structure is very flexible because of features that allow adapting via learning and adjustment of the used knowledge. Therefore, the proposed structure may be used in environments with stochastic features such as hardly predictable events or elements. The basic elements of the proposed structure have found their implementation in software system and experimental robotic system. The software system as well as the robotic system has been used for experimentation in order to validate the proposed structure - its functionality, flexibility and reliability. Both of them are presented in the paper. The basic features of each system are presented as well. The most important results of experiments are outlined and discussed at the end of the paper. Some possible directions of further research are also sketched at the end of the paper.

The use of presidential executive orders to control the management and administration of the federal government

As long as governmental institutions have existed, efforts have been undertaken to reform them. This research examines a particular strategy, coercive controls, exercised through a particular instrument, executive orders, by a singular reformer, the president of the United States. The presidents studied-- Johnson, Nixon, Ford, Carter, Reagan, Bush, and Clinton--are those whose campaigns for office were characterized to varying degrees as against Washington bureaucracy and for executive reform. Executive order issuance is assessed through an examination of key factors for each president including political party affiliation, levels of political capital, and legislative experience. A classification typology is used to identify the topical dimensions and levels of coerciveness. The portrayal of the federal government is analyzed through examination of public, media, and presidential attention. The results show that executive orders are significant management tools for the president. Executive orders also represent an important component of the transition plans for incoming administrations. The findings indicate that overall, while executive orders have not increased in the aggregate, they are more intrusive and significant. When the factors of political party affiliation, political capital, and legislative experience are examined, it reveals a strong relationship between executive orders and previous executive experience, specifically presidents who served as a state governor prior to winning national election as president. Presidents Carter, Reagan, and Clinton (all former governors) have the highest percent of executive orders focusing on the federal bureaucracy. Additionally, the highest percent of forceful orders were issued by former governors (41.0%) as compared to their presidential counterparts who have not served as governors (19.9%). Secondly, political party affiliation is an important, but not significant, predictor for the use of executive orders. Thirdly, management strategies that provide the president with the greatest level of autonomy--executive orders--redefine the concept of presidential power and autonomous action. Interviews of elite government officials and political observers support the idea that executive orders can provide the president with a successful management strategy, requiring less expenditure of political resources, less risk to political capital, and a way of achieving objectives without depending on an unresponsive Congress. ^

The use of presidential executive orders to control the management and administration of the federal government

As long as governmental institutions have existed, efforts have been undertaken to reform them. This research examines a particular strategy, coercive controls, exercised through a particular instrument, executive orders, by a singular reformer, the president of the United States. The presidents studied- Johnson, Nixon, Ford, Carter, Reagan, Bush, and Clinton-are those whose campaigns for office were characterized to varying degrees as against Washington bureaucracy and for executive reform. Executive order issuance is assessed through an examination of key factors for each president including political party affiliation, levels of political capital, and legislative experience. A classification typology is used to identify the topical dimensions and levels of coerciveness. The portrayal of the federal government is analyzed through examination of public, media, and presidential attention. The results show that executive orders are significant management tools for the president. Executive orders also represent an important component of the transition plans for incoming administrations. The findings indicate that overall, while executive orders have not increased in the aggregate, they are more intrusive and significant. When the factors of political party affiliation, political capital, and legislative experience are examined, it reveals a strong relationship between executive orders and previous executive experience, specifically presidents who served as a state governor prior to winning national election as president. Presidents Carter, Reagan, and Clinton (all former governors) have the highest percent of executive orders focusing on the federal bureaucracy. Additionally, the highest percent of forceful orders were issued by former governors (41.0%) as compared to their presidential counterparts who have not served as governors (19.9%). Secondly, political party affiliation is an important, but not significant, predictor for the use of executive orders. Thirdly, management strategies that provide the president with the greatest level of autonomy-executive orders redefine the concept of presidential power and autonomous action. Interviews of elite government officials and political observers support the idea that executive orders can provide the president with a successful management strategy, requiring less expenditure of political resources, less risk to political capital, and a way of achieving objectives without depending on an unresponsive Congress.

Admittance Control for Robotic Loading: Design and Experiments with a 1-Tonne Loader and a 14-Tonne LHD

This paper describes the design, tuning, and extensive field testing of an admittance-based Autonomous Loading Controller (ALC) for robotic excavation. Several iterations of the ALC were tuned and tested in fragmented rock piles—similar to those found in operating mines—by using both a robotic 1-tonne capacity Kubota R520S diesel-hydraulic surface loader and a 14-tonne capacity Atlas Copco ST14 underground load-haul-dump (LHD) machine. On the R520S loader, the ALC increased payload by 18 % with greater consistency, although with more energy expended and longer dig times when compared with digging at maximum actuator velocity. On the ST14 LHD, the ALC took 61 % less time to load 39 % more payload when compared to a single manual operator. The manual operator made 28 dig attempts by using three different digging strategies, and had one failed dig. The tuned ALC made 26 dig attempts at 10 and 11 MN target force levels. All 10 11 MN digs succeeded while 6 of the 16 10 MN digs failed. The results presented in this paper suggest that the admittance-based ALC is more productive and consistent than manual operators, but that care should be taken when detecting entry into the muck pile

Geometric versus Model Predictive Control based guidance algorithms for fixed-wing UAVs in the presence of very strong wind fields.

The recent years have witnessed increased development of small, autonomous fixed-wing Unmanned Aerial Vehicles (UAVs). In order to unlock widespread applicability of these platforms, they need to be capable of operating under a variety of environmental conditions. Due to their small size, low weight, and low speeds, they require the capability of coping with wind speeds that are approaching or even faster than the nominal airspeed. In this thesis, a nonlinear-geometric guidance strategy is presented, addressing this problem. More broadly, a methodology is proposed for the high-level control of non-holonomic unicycle-like vehicles in the presence of strong flowfields (e.g. winds, underwater currents) which may outreach the maximum vehicle speed. The proposed strategy guarantees convergence to a safe and stable vehicle configuration with respect to the flowfield, while preserving some tracking performance with respect to the target path. As an alternative approach, an algorithm based on Model Predictive Control (MPC) is developed, and a comparison between advantages and disadvantages of both approaches is drawn. Evaluations in simulations and a challenging real-world flight experiment in very windy conditions confirm the feasibility of the proposed guidance approach.

Planificación económica y control democrático del mercado

El cuestionamiento de las relaciones capitalistas de producción debe surgir a partir de su tendencia inherente a los desequilibrios y a la irracionalidad económica y no desde algún pre-juicio ideológico o político. En este contexto, la planificación económica se presenta como necesaria en la medida en que se requiera asegurar una autonomía humana de decisión con respecto a la distribución del ingreso, el acceso al empleo y la protección del medio ambiente. A partir de la constatación de este hecho, la planificación no sustituye a las relaciones mercantiles sino que cumple la función de garantizar una tendencia al equilibrio sobre la base de las relaciones mercantiles, lo que ningún automatismo del mercado puede garantizar. Se propone un principio de delimitación entre la planificación y la autonomía de las empresas (la reproducción de la vida humana), principio ampliable a la delimitación entre el Estado y las actividades de los grupos autónomos y de los mismos sujetos en general. Abstract The questioning of the capitalist relations of production must come from their inherent tendency to irrationality and economic imbalances and not from any ideological or political prejudice. In this context, economic planning is as necessary as it is required to ensure a human decision-making autonomy with respect to income distribution, access to employment and environmental protection. From the observation of this fact, planning is not a substitute for market relations but serves to ensure a tendency to balance on the basis of market relations, so no automatic of the market can guarantee. The article proposes a principle of demarcation between the planning and autonomy for enterprises (the reproduction of human life), expandable to top the demarcation between the state and the activities of autonomous groups and the same subjects in general.

Multirobot Tethering for Localization and Control

Particle filtering has proven to be an effective localization method for wheeled autonomous vehicles. For a given map, a sensor model, and observations, occasions arise where the vehicle could equally likely be in many locations of the map. Because particle filtering algorithms may generate low confidence pose estimates under these conditions, more robust localization strategies are required to produce reliable pose estimates. This becomes more critical if the state estimate is an integral part of system control. We investigate the use of particle filter estimation techniques on a hovercraft vehicle. The marginally stable dynamics of a hovercraft require reliable state estimates for proper stability and control. We use the Monte Carlo localization method, which implements a particle filter in a recursive state estimate algorithm. An H-infinity controller, designed to accommodate the latency inherent in our state estimation, provides stability and controllability to the hovercraft. In order to eliminate the low confidence estimates produced in certain environments, a multirobot system is designed to introduce mobile environment features. By tracking and controlling the secondary robot, we can position the mobile feature throughout the environment to ensure a high confidence estimate, thus maintaining stability in the system. A laser rangefinder is the sensor the hovercraft uses to track the secondary robot, observe the environment, and facilitate successful localization and stability in motion.

Dissecting signaling pathways that control glia migration in the developing Drosophila retina

The function of a complex nervous system relies on an intricate interaction between neurons and glial cells. However, as glial cells are generally born distant from the place where they settle, molecular cues are important to direct their migration. Glial cell migration is important in both normal development and disease, thus current research in the laboratory has been focused on dissecting regulatory events underlying that crucial process. With this purpose, the Drosophila eye imaginal disc has been used as a model. In response to neuronal photoreceptor differentiation, glial cells migrate from the CNS into the eye disc where they act to correctly wrap axons. To ensure proper development, attractive and repulsive signals must coordinate glial cell migration. Importantly, one of these signals is Bnl, a Fibroblast Growth Factor (FGF) ligand expressed by retinal progenitor cells that was suggested to act as a non-autonomous negative regulator of excessive glial cell migration (overmigration) by binding and activating the Btl receptor expressed by glial cells. Through the experimental results described in chapter 3 we gained a detailed insight into the function of bnl in eye disc growth, photoreceptor development, and glia migration. Interestingly, we did not find a direct correlation between the defects on the ongoing photoreceptors and the glia overmigration phenotype; however, bnl knockdown caused apoptosis of eye progenitor cells what was strongly correlated with glia migration defects. Glia overmigration due to Bnl down-regulation in eye progenitor cells was rescued by inhibiting the pro-apoptotic genes or caspases activity, as well as, by depleting JNK or Dp53 function in retinal progenitor cells. Thus, we suggest a cross-talk between those developmental signals in the control of glia migration at a distance. Importantly, these results suggest that Bnl does not control glial migration in the eye disc exclusively through its ability to bind and activate its receptor Btl in glial cells. We also discuss possible biological roles for the glia overmigration in the bnl knockdown background. Previous results in the lab showed an interaction between dMyc, a master regulator of tissue growth, and Dpp, a Transforming Growth Factor-β important for retinal patterning and for accurate glia migration into the eye disc. Thus, we became interested in understanding putative relationships between Bnl and dMyc. In chapter 4, we show that they positively cooperate in order to ensure proper development of the eye disc. This work highlights the importance of the FGF signaling in eye disc development and reveals a signaling network where a range of extra- and intra-cellular signals cooperate to non-autonomously control glial cell migration. Therefore, such inter-relations could be important in other Drosophila cellular contexts, as well as in vertebrate tissue development.

Exploring coordination-driven self-assembly with autonomous chemical robots

The work presented herein focused on the automation of coordination-driven self assembly, exploring methods that allow syntheses to be followed more closely while forming new ligands, as part of the fundamental study of the digitization of chemical synthesis and discovery. Whilst the control and understanding of the principle of pre-organization and self-sorting under non-equilibrium conditions remains a key goal, a clear gap has been identified in the absence of approaches that can permit fast screening and real-time observation of the reaction process under different conditions. A firm emphasis was thus placed on the realization of an autonomous chemical robot, which can not only monitor and manipulate coordination chemistry in real-time, but can also allow the exploration of a large chemical parameter space defined by the ligand building blocks and the metal to coordinate. The self-assembly of imine ligands with copper and nickel cations has been studied in a multi-step approach using a self-built flow system capable of automatically controlling the liquid-handling and collecting data in real-time using a benchtop MS and NMR spectrometer. This study led to the identification of a transient Cu(I) species in situ which allows for the formation of dimeric and trimeric carbonato bridged Cu(II) assemblies. Furthermore, new Ni(II) complexes and more remarkably also a new binuclear Cu(I) complex, which usually requires long and laborious inert conditions, could be isolated. The study was then expanded to the autonomous optimization of the ligand synthesis by enabling feedback control on the chemical system via benchtop NMR. The synthesis of new polydentate ligands has emerged as a result of the study aiming to enhance the complexity of the chemical system to accelerate the discovery of new complexes. This type of ligand consists of 1-pyridinyl-4-imino-1,2,3-triazole units, which can coordinate with different metal salts. The studies to test for the CuAAC synthesis via microwave lead to the discovery of four new Cu complexes, one of them being a coordination polymer obtained from a solvent dependent crystallization technique. With the goal of easier integration into an automated system, copper tubing has been exploited as the chemical reactor for the synthesis of this ligand, as it efficiently enhances the rate of the triazole formation and consequently promotes the formation of the full ligand in high yields within two hours. Lastly, the digitization of coordination-driven self-assembly has been realized for the first time using an in-house autonomous chemical robot, herein named the ‘Finder’. The chemical parameter space to explore was defined by the selection of six variables, which consist of the ligand precursors necessary to form complex ligands (aldehydes, alkineamines and azides), of the metal salt solutions and of other reaction parameters – duration, temperature and reagent volumes. The platform was assembled using rounded bottom flasks, flow syringe pumps, copper tubing, as an active reactor, and in-line analytics – a pH meter probe, a UV-vis flow cell and a benchtop MS. The control over the system was then obtained with an algorithm capable of autonomously focusing the experiments on the most reactive region (by avoiding areas of low interest) of the chemical parameter space to explore. This study led to interesting observations, such as metal exchange phenomena, and also to the autonomous discovery of self assembled structures in solution and solid state – such as 1-pyridinyl-4-imino-1,2,3-triazole based Fe complexes and two helicates based on the same ligand coordination motif.

Spatial dynamics of bovine tuberculosis in the Autonomous Community of Madrid, Spain (2010-2012)

Progress in control of bovine tuberculosis (bTB) is often not uniform, usually due to the effect of one or more sometimes unknown epidemiological factors impairing the success of eradication programs. Use of spatial analysis can help to identify clusters of persistence of disease, leading to the identification of these factors thus allowing the implementation of targeted control measures, and may provide some insights of disease transmission, particularly when combined with molecular typing techniques. Here, the spatial dynamics of bTB in a high prevalence region of Spain were assessed during a three year period (2010-2012) using data from the eradication campaigns to detect clusters of positive bTB herds and of those infected with certain Mycobacterium bovis strains (characterized using spoligotyping and VNTR typing). In addition, the within-herd transmission coefficient (β) was estimated in infected herds and its spatial distribution and association with other potential outbreak and herd variables was evaluated. Significant clustering of positive herds was identified in the three years of the study in the same location ("high risk area"). Three spoligotypes (SB0339, SB0121 and SB1142) accounted for >70% of the outbreaks detected in the three years. VNTR subtyping revealed the presence of few but highly prevalent strains within the high risk area, suggesting maintained transmission in the area. The spatial autocorrelation found in the distribution of the estimated within-herd transmission coefficients in herds located within distances <14 km and the results of the spatial regression analysis, support the hypothesis of shared local factors affecting disease transmission in farms located at a close proximity.

A second order control-volume finite-element least-squares strategy for simulating diffusion in strongly anisotropic media

An unstructured mesh �nite volume discretisation method for simulating di�usion in anisotropic media in two-dimensional space is discussed. This technique is considered as an extension of the fully implicit hybrid control-volume �nite-element method and it retains the local continuity of the ux at the control volume faces. A least squares function recon- struction technique together with a new ux decomposition strategy is used to obtain an accurate ux approximation at the control volume face, ensuring that the overall accuracy of the spatial discretisation maintains second order. This paper highlights that the new technique coincides with the traditional shape function technique when the correction term is neglected and that it signi�cantly increases the accuracy of the previous linear scheme on coarse meshes when applied to media that exhibit very strong to extreme anisotropy ratios. It is concluded that the method can be used on both regular and irregular meshes, and appears independent of the mesh quality.