Thermomechanical analysis of strain localization in a ductile detachment zone

At the latitude of the Thor-Odin dome (British Columbia) the Columbia River Detachment defines the eastern margin of the Shuswap metamorphic core complex and localizes in a 1 km thick muscovite-bearing quartzite mylonite. We present a combined Ar-40/Ar-39, (micro) structural, and oxygen isotope study of the deformation history in the detachment and evaluate the spatial and temporal relationships between microstructure formation and localization of strain. High-precision Ar-40/Ar-39 geochronology from different levels in the mylonite delineates a pattern of increasingly younger (49.0 to 47.9 Ma) deformation ages in deeper levels of the mylonitic footwall. The correlation of Ar-40/Ar-39 ages with decreasing deformation temperatures (similar to 550 degrees-400 degrees C) in the top 200 m of the mylonite indicates that deformation migrated downward from the contact with the hanging wall. Strain localization was diachronous in progressively deeper levels of the footwall and was likely controlled by fluid-assisted strain hardening due to advective heat removal and contemporaneous reaction weakening due to dissolution-reprecipitation of white mica. The observed constant high-stress microstructures across the entire detachment indicate that flow stress was buffered by the interplay of strain rate and temperature, where high strain rates at elevated temperature produced the same microstructure as lower strain rates under decreasing temperature conditions. The combined data suggest that the complex interplay among temporally nonuniform rates of footwall exhumation, heat advection, and embrittlement by meteoric fluids strongly determines the thermomechanical behavior of extensional detachments.

Tonoplast localization of a calmodulin-stimulated Ca2+-pump from maize roots.

The subcellular localization of a calmodulin-stimulated calcium (Ca2+)-ATPase activity from maize roots (Zea mays L., cv LG 11) was studied. For this purpose, an efficient procedure was developed to prepare sealed plasma membrane vesicles allowing the measurement of proton and Ca2+ transport activities. Two-day-old root membranes were fractionated by sucrose and dextran density gradient centrifugation. Marker enzymes were used to study the distribution of the different membranes in the gradients and a filtration technique was developed to measure Ca-45(2+) transport in sealed vesicles. Most of the ATP-dependent Ca2+ transport activity was associated with the ER. However, a small part of this activity was associated with the tonoplast (corresponding to the activity of the H+/Ca2+ antiport) and the plasma membrane. When the Ca2+ transport was measured in the presence of exogenous calmodulin (1 muM), a 3-5-fold increase of uptake was measured. The calmodulin-stimulated activity was associated with the tonoplast vesicles only. This activity was insensitive to monensin, a proton ionophore, ruling out a direct effect of calmodulin on the H+/Ca2+ antiport. In conclusion, four different Ca2+ transporters are present in young maize root cells. A Ca2+/H+ antiport system is present on the tonoplast, whereas, the plasma membrane and the ER possess each a calmodulinin-sensitive Ca2+-ATPase. Finally, a calmodulin-stimulated Ca2+-ATPase is associated with the tonoplast.

Subcellular localization, distribution and expression of calmodulin in Zea mays roots.

The subcellular localization, distribution and the steady state level of calmodulin from maize roots (Zea mays L., cv. LG 11) were studied. To analyze the subcellular localization, 2-day old root membranes were fractionated by sucrose density gradient centrifugation and immunoblotting was done with an antibody raised against a vertebrate calmodulin (SWant) which recognized the plant calmodulin. Calmodulin was principally associated with high density fractions and particularly plasmalemma. For studying the distribution of calmodulin in various zones of Zea mays roots, a micro method of membrane preparation was developed. Most of the calmodulin was present in microsomes isolated from the root apex corresponding to the first 4 mm of a 15 +/- 2 mm root. An identical distribution was found by studying the steady state level of the protein by Northern blotting using a cDNA clone of Zea mays calmodulin.

Differential epipolar constraint in mobile robot egomotion estimation

The estimation of camera egomotion is a well established problem in computer vision. Many approaches have been proposed based on both the discrete and the differential epipolar constraint. The discrete case is mainly used in self-calibrated stereoscopic systems, whereas the differential case deals with a unique moving camera. The article surveys several methods for mobile robot egomotion estimation covering more than 0.5 million samples using synthetic data. Results from real data are also given

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

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

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

Experimental Modeling and Control Strategies on an Open Mobile Robot Platform PRIM

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system

PRIM an Open Mobile Robot Platform. Motivation, Present and Future Trends

This paper is focused on the robot mobile platform PRIM (platform robot information multimedia). This robot has been made in order to cover two main needs of our group, on one hand the need for a full open mobile robotic platform that is very useful in fulfilling the teaching and research activity of our school community, and on the other hand with the idea of introducing an ethical product which would be useful as mobile multimedia information point as a service tool. This paper introduces exactly how the system is made up and explains just what the philosophy is behind this work. The navigation strategies and sensor fusion, where machine vision system is the most important one, are oriented towards goal achievement and are the key to the behaviour of the robot

Knowledge integration within an applied mobile robot summer course

This paper presents the use of a mobile robot platform as an innovative educational tool in order to promote and integrate different curriculum knowledge. Hence, it is presented the acquired experience within a summer course named ldquoapplied mobile roboticsrdquo. The main aim of the course is to integrate different subjects as electronics, programming, architecture, perception systems, communications, control and trajectory planning by using the educational open mobile robot platform PRIM. The summer course is addressed to a wide range of student profiles. However, it is of special interests to the students of electrical and computer engineering around their final academic year. The summer course consists of the theoretical and laboratory sessions, related to the following topics: design & programming of electronic devices, modelling and control systems, trajectory planning and control, and computer vision systems. Therefore, the clues for achieving a renewed path of progress in robotics are the integration of several knowledgeable fields, such as computing, communications, and control sciences, in order to perform a higher level reasoning and use decision tools with strong theoretical base

A Camera-Projector System for Robot Positioning by Visual Servoing

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance