Connectivity from source to sink in a lowland area: the Loire river basin (France)

Sediment connectivity relates to the transfer of sediments from sources to sinks via runoff and in channel transport. It is highly dependent on spatial variability of landscape properties such as differences in morphology, land use and infiltration/runoff characteristics but may also vary in time due to differences in rainfall amount/intensity and changes in vegetation cover throughout the year. In the Loire river basin, we found that sediment fluxes displayed strong variations in space but also at the interannual and seasonnal time scales (Gay et al. 2013). In this context, our goal is to better understand and quantify hillslope sediment redistributions within this lowland area thanks to the use of semi distributed connectivity approach. To this aim, Borselli's index of connectivity (IC, Borselli et al., 2008) is selected to assess hillslope connectivity at annual and seasonal time scales. Several improvements are proposed to take into account the coupling of the structural landscape connectivity and its hydrosedimentary response. Parameters such as rainfall intensity and differences in seasonal land cover are integrated into the model to account for landscape variations through time. Infiltration and runoff indices were also tested. Preliminary results confirm the variability of landscape connectivity throughout the year. The integration of the index of infiltration and runoff properties of landscape (IDPR) as defined by Mardhel et al. 2004 seems to improve the IC model outputs. From this first step, in-stream sediment connectivity index should be developed for a better understanding and assessment of sediment redistributions at the entire catchment scal

Simbatch: an API for simulating and predicting the performance of parallel resources and batch systems

The study of scheduling algorithms for parallel tasks in a grid computing context either neglects local reservation systems which manage parallel resources, either suppose that they use a First Come First Served strategy, or the experimental model does not handle parallel tasks. In this report, we describe an API built in the grid simulation tool Simgrid. It offers core functionalities to simulate in a realistic way parallel resources and batch reservation systems. Simbatch simulation experiments show an error rate inferior to 1% compared to real life experiments conducted with the OAR batch manager

Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

In this paper we present a framework to learn a model-free feedback controller for locomotion and balance control of a compliant quadruped robot walking on rough terrain. Having designed an open-loop gait encoded in a Central Pattern Generator (CPG), we use a neural network to repre- sent sensory feedback inside the CPG dynamics. This neural network accepts sensory inputs from a gyroscope or a camera, and its weights are learned using Particle Swarm Optimization (unsupervised learning). We show with a simulated compliant quadruped robot that our controller can perform significantly better than the open-loop one on slopes and randomized height maps

Towards simple control for complex, autonomous robotic applications: Combining discrete and rhythmic motor primitives

Vertebrates are able to quickly adapt to new environments in a very robust, seemingly effortless way. To explain both this adaptivity and robustness, a very promising perspective in neurosciences is the modular approach to movement generation: Movements results from combinations of a finite set of stable motor primitives organized at the spinal level. In this article we apply this concept of modular generation of movements to the control of robots with a high number of degrees of freedom, an issue that is challenging notably because planning complex, multidimensional trajectories in time-varying environments is a laborious and costly process.We thus propose to decrease the complexity of the planning phase through the use of a combination of discrete and rhythmic motor primitives, leading to the decoupling of the planning phase (i.e. the choice of behavior) and the actual trajectory generation. Such implementation eases the control of, and the switch between, different behaviors by reducing the dimensionality of the high-level commands.Moreover, since the motor primitives are generated by dynamical systems, the trajectories can be smoothly modulated, either by high-level commands to change the current behavior or by sensory feedback information to adapt to environmental constraints. In order to show the generality of our approach, we apply the framework to interactive drumming and infant crawling in a humanoid robot. These experiments illustrate the simplicity of the control architecture in terms of planning, the integration of different types of feedback (vision and contact) and the capacity of autonomously switching between different behaviors (crawling and simple reaching)

Comparative evaluation of approaches in T.4.1-4.3 and working definition of adaptive module

The goal of this deliverable is two-fold: (1) to present and compare different approaches towards learning and encoding movements us- ing dynamical systems that have been developed by the AMARSi partners (in the past during the first 6 months of the project), and (2) to analyze their suitability to be used as adaptive modules, i.e. as building blocks for the complete architecture that will be devel- oped in the project. The document presents a total of eight approaches, in two groups: modules for discrete movements (i.e. with a clear goal where the movement stops) and for rhythmic movements (i.e. which exhibit periodicity). The basic formulation of each approach is presented together with some illustrative simulation results. Key character- istics such as the type of dynamical behavior, learning algorithm, generalization properties, stability analysis are then discussed for each approach. We then make a comparative analysis of the different approaches by comparing these characteristics and discussing their suitability for the AMARSi project

Integration of vision and central pattern generator based locomotion for path planning of a non-holonomic crawling humanoid robot

In this paper we present our work on integrating a locomotion controller based on central pattern generator (CPG) and a motion planning algorithm using artificial potential fields for a non-holonomic crawling humanoid robot, the iCub. We also integrated a vision tracker and an inverse kinematics solver to perform reaching tasks. We study the influence of the various parameters of the potential field equations on the performance of the system and prove the efficiency of our framework by testing it on a physics-based robotics simulator and partially on the real iCub

Model-Based and Model-Free Approaches for Postural Control of a Compliant Humanoid Robot using Optical Flow

Vision is a very rich sensor with a proven critical role in the control of balance. However, it is widely under- used for robotics postural control. This paper presents and compares two approaches, one model-based and one model-free, to ensure stability of the COMAN compliant humanoid robot standing on a moving platform. The model-based approach uses inverse kinematics, while the model-free one relies on a neural network as mapping between sensors and actuators. The sensory information is composed of proprioceptive cues (gyroscope) and visual cues, used separately or together. We present methods of using vision as sensory input without relying on a particular object or feature of the scene, but only on the optical flow. The performance of both approaches are compared systematically in a realistic robotics simulator, for different movements of the platform and using different sensory cues. We aim to see if vision can replace proprioceptive sensors or be fused with them to improve the performance of the stabilizing controller. While both model-based and model-free approaches successfully stabilize the robot, the model-free approach shows better overall performance. Preliminary results on the real COMAN robot are show

Towards Modular Control for Moderately Fast Locomotion over Unperceived Rough Terrain

We are motivated to build simple controllers for quadruped robots to locomote over unperceived moderately difficult rough terrain at moderately fast speeds. The presented approach here does not need force sensing at feet, and does not need information about the mass properties of the robot like inertia tensors, so it is apt for relatively cheap and lightweight robots. We explore our approach with two dif- ferent simulated robots, one being the simulation of the Oncilla robot which will soon be used for validation

Aspergillus PCR in Bronchoalveolar Lavage Fluid for the Diagnosis and Prognosis of Aspergillosis in Patients With Hematological and Non-hematological Conditions

Objectives: We evaluated the usefulness of an Aspergillus fumigatus quantitative PCR assay performed in bronchoalveolar lavage fluid (BAL) for the diagnosis and prognosis of both invasive and non-invasive aspergillosis.Methods: This 4-year retrospective study involved 613 at-risk patients who had either hematological disorders or other immunosuppressive conditions, notably solid organ transplants. Thirty-five patients had proven/probable aspergillosis and thirteen had chronic non-invasive aspergillosis. We compared PCR, galactomannan index and mycological analysis of BAL.Results: For invasive aspergillosis (IA), PCR performed in BAL yielded 88.6% sensitivity and 95.5% specificity. Comparatively, galactomannan index and mycological examination yielded only 56.3 and 63.6% sensitivity and 97.6 and 94.5% specificity, respectively. Considering the 13 chronic aspergillosis cases, PCR, galactomannan index and mycological examination yielded 76.9, 15.4, and 84.6% sensitivity and 92.2, 94.9, and 93% specificity, respectively. Fungal load in BAL evaluated by PCR was able to discriminate between aspergillosis and contamination, but not between invasive and non-invasive forms. Finally, fungal load was predictive of 90-day mortality, with 23.1% mortality for patients with less than 500 copies/mL versus 68.4% for patients above that cut-off (p < 0.05).Conclusion: Our results indicate that Aspergillus PCR in BAL is of particular interest for both the diagnosis and the prognosis of IA. It is likewise an interesting tool for the diagnosis of non-invasive forms