The philosophical foundations of classical "rDzogs chen" in Tibet : investigating the distinction between dualistic mind (sems) and primordial knowing (ye shes)

While the syncretistic Tibetan tradition known as rDzogs chen ("Great Perfection") has attracted considerable attention over the past few decades, its philosophical foundations remain largely unknown to those unacquainted with its primary sources. This thesis looks at the essentials of rDzogs chen philosophy through the lens of two principal distinctions that the tradition has considered indispensable for understanding its distinctive views and practices: dualistic mind (sems) versus primordial knowing (ye shes) and dharmakâya versus the 'ground of all' (kun gzhi) conditioned experience. Arguing that the distinctions provided classical rDzogs chen scholars with a crucial framework for (a) articulating the necessary conditions of nondual primordial knowing, the conditio sine qua non of rNying ma soteriology, and (b) schematizing the relationship between the exoteric and esoteric vehicles of Indian Buddhism within a unifying conception of the Buddhist path as the progressive disclosure of primordial knowing, the thesis shows how the rDzogs chen philosophy of mind has been integral to the tradition's complex soteriology. The thesis consists of two parts: (1) a detailed philosophical investigation of the distinctions and (2) an anthology of previously untranslated Tibetan materials on the distinctions accompanied by critical editions and introductions. The first part systematically invesigates the nature and scope of the distinctions and traces their evolution and complex relationships with Indian Buddhist Cittamâtra, Madhyamaka, Pramàriavàda, and Vajrayâna views. It concludes with an exploration of some soteriological implications of the mind/primordial knowing distinction that became central to rDzogs chen path hermeneutics in the classical period as authors of rDzogs chen path summaries used this distinction to reconcile progressivist sutric and non-progressivist tantric models of the Buddhist path. The translations and texts included in part two of the thesis consist of (a) a short treatise from Klong chen pa's Miscellaneous Writings entitled Sems dang ye shes kyi dris lan (Reply to Questions Concerning Mind and Primordial Knowing), (b) selected passages on the distinctions from this author's monumental summary of the rDzogs chen snying thig system, the Theg mchog mdzod (Treasury of the Supreme Vehicle), and (c) an excerpt on rDzogs chen distinctions taken from 'Jigs med gling pa's (1729-1798) 18th century Klong chen sNying thig path summary entitled Treasury of Qualities (Yon tan mdzod) along with a word-by- word commentary by Yon tan rgya mtsho (b. 19th c.).

BCN-Routing : càlcul web de rutes amb pgRouting, OpenStreetMaps i OpenLayers

Es presenta un sistema acurat de càlcul web d'itineraris mínims (per a vianants i per a vehicles) entre dos punts de la ciutat de Barcelona, un dels quals es triat per l'usuari directament a sobre un mapa i l'altre, alternativament, a sobre el mateix mapa o bé a sobre una llista de selecció de les principals atraccions turístiques de Barcelona.El sistema es troba implementat per medi de MapServer (1) com a servidor, OpenLayers (2) per a la interfície d'usuari, una base de dades PostrgreSQL (3)/PostGIS (4) que recull dades d'OpenStreetMaps (5) per a la navegació i dades introduïdes manualment, per a la llista de selecció d'atraccions turístiques. Per al càlcul d'itineraris es fa servir, pgRouting (6) alhora que s'accedeix a la cartografia de CartoCiudad (7) per a mostrar un mapa de base i opcionalment els noms dels carrers i punts d'interès a partir de les capes FondoUrbano, Vial i Topónimo del servidor WMS de CartoCiudad.Tot el sistema corre a sobre Windows 7 Home Premium (8).Així mateix es presenten quatre noves funcions i un tipus definit per l'usuari de PostgreSQL per al càlcul acurat d'itineraris mínims i l'estudi teòric que justifica la seva bondat.

Speciation of antimony (III) and antimony (V) using hydride generation for meglumine antimoniate pharmaceutical formulationsquality control

The pentavalent antimonies, mainly the meglumine antimoniate, are recommends as first-choice medicines for leishmaniasis therapy. In this work we described the development of formulations of meglumine antimoniate injectable medication, as well as the analytical methodology used in the selective determination of Sb(III) and Sb(Total) by hydride generation - inductively coupled plasma atomic emission spectrometry (HG-ICP-AES) and ICP-AES, respectively. On that purpose the analytical methodology was developed focusing on the HG-ICP-AES technique. The formulations using propylene glycol/water as vehicles in a 20:80 proportion were more appropriate for subsequent use in industrial scale. These formulations also showed a lower variation on Sb(III) percentage, no need of buffer solution to stabilize the formulation and no influence of the autoclaving in the quality of the product. The results of the development of the analytical methodology point out the proposed method as an efficient alternative for the determination of Sb(III) in the presence of large quantities of Sb(V) in injectable solutions of meglumine antimoniate, in a selective, linear, accurate and precise manner. In addition, the method showed a low limit of quantification, less interference of the matrix, and more resilience than batch techniques proposed in the Brazilian Pharmacopeia.

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Vision-based localization of an underwater robot in a structured environment

This paper presents a vision-based localization approach for an underwater robot in a structured environment. The system is based on a coded pattern placed on the bottom of a water tank and an onboard down looking camera. Main features are, absolute and map-based localization, landmark detection and tracking, and real-time computation (12.5 Hz). The proposed system provides three-dimensional position and orientation of the vehicle along with its velocity. Accuracy of the drift-free estimates is very high, allowing them to be used as feedback measures of a velocity-based low-level controller. The paper details the localization algorithm, by showing some graphical results, and the accuracy of the system

An approach to vision-based station keeping for an unmanned underwater vehicle

This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Perspectives of auto-correcting lens distortions in mosaic-based underwater navigation

When unmanned underwater vehicles (UUVs) perform missions near the ocean floor, optical sensors can be used to improve local navigation. Video mosaics allow to efficiently process the images acquired by the vehicle, and also to obtain position estimates. We discuss in this paper the role of lens distortions in this context, proving that degenerate mosaics have their origin not only in the selected motion model or in registration errors, but also in the cumulative effect of radial distortion residuals. Additionally, we present results on the accuracy of different feature-based approaches for self-correction of lens distortions that may guide the choice of appropriate techniques for correcting distortions

A system to evaluate the accuracy of a visual mosaicking methodology

When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system

Estimating the motion of an underwater robot from a monocular image sequence

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot

Correction of shading effects in vision-based UUV localization

This paper describes the improvements achieved in our mosaicking system to assist unmanned underwater vehicle navigation. A major advance has been attained in the processing of images of the ocean floor when light absorption effects are evident. Due to the absorption of natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination for processing underwater images. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion. In this paper a technique to correct non-uniform lighting is proposed. The acquired frames are compensated through a point-by-point division of the image by an estimation of the illumination field. Then, the gray-levels of the obtained image remapped to enhance image contrast. Experiments with real images are presented

On the way to solve lighting problems in underwater imaging

A major obstacle to processing images of the ocean floor comes from the absorption and scattering effects of the light in the aquatic environment. Due to the absorption of the natural light, underwater vehicles often require artificial light sources attached to them to provide the adequate illumination. Unfortunately, these flashlights tend to illuminate the scene in a nonuniform fashion, and, as the vehicle moves, induce shadows in the scene. For this reason, the first step towards application of standard computer vision techniques to underwater imaging requires dealing first with these lighting problems. This paper analyses and compares existing methodologies to deal with low-contrast, nonuniform illumination in underwater image sequences. The reviewed techniques include: (i) study of the illumination-reflectance model, (ii) local histogram equalization, (iii) homomorphic filtering, and, (iv) subtraction of the illumination field. Several experiments on real data have been conducted to compare the different approaches

Probabilistic sonar scan matching for an AUV

This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results

VLSI architecture for an Underwater Robot Vision System

It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great number of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. For normalised correlation criteria, previous experiments shown that the result is not altered in presence of nonuniform illumination. Usually, hardware for motion estimation has been limited to simple correlation criteria. The main goal of this paper is to propose a VLSI architecture for motion estimation using a matching criteria more complex than Sum of Absolute Differences (SAD) criteria. Today hardware devices provide many facilities for the integration of more and more complex designs as well as the possibility to easily communicate with general purpose processors