The Ariadne's Clew Algorithm

We present a new approach to path planning, called the "Ariadne's clew algorithm". It is designed to find paths in high-dimensional continuous spaces and applies to robots with many degrees of freedom in static, as well as dynamic environments - ones where obstacles may move. The Ariadne's clew algorithm comprises two sub-algorithms, called Search and Explore, applied in an interleaved manner. Explore builds a representation of the accessible space while Search looks for the target. Both are posed as optimization problems. We describe a real implementation of the algorithm to plan paths for a six degrees of freedom arm in a dynamic environment where another six degrees of freedom arm is used as a moving obstacle. Experimental results show that a path is found in about one second without any pre-processing

Obstacle Avoidance and Proscriptive Bayesian Programming

Unexpected events and not modeled properties of the robot environment are some of the challenges presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a probabilistic approach called Bayesian Programming, which aims to deal with the uncertainty, imprecision and incompleteness of the information handled to solve the obstacle avoidance problem. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. A video illustration of the developed experiments can be found at http://www.inrialpes.fr/sharp/pub/laplac

Using Bayesian Programming for Multisensor Multi-Target Tracking in Automative Applications

A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. Carsense is a European project whose purpose is to develop such a new sensing system. It will combine different sensors (laser, radar and video) and will rely on the fusion of the information coming from these sensors in order to achieve better accuracy, robustness and an increase of the information content. This paper demonstrates the interest of using probabilistic reasoning techniques to address this challenging multi-sensor data fusion problem. The approach used is called Bayesian Programming. It is a general approach based on an implementation of the Bayesian theory. It was introduced rst to design robot control programs but its scope of application is much broader and it can be used whenever one has to deal with problems involving uncertain or incomplete knowledge

Proscriptive Bayesian Programming Application for Collision Avoidance

Evolve safely in an unchanged environment and possibly following an optimal trajectory is one big challenge presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a solution based on a probabilistic approach called Bayesian Programming. This approach aims to deal with the uncertainty, imprecision and incompleteness of the information handled. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. Some videos illustrating these experiments can be found at http://www-laplace.imag.fr

The Design and Implementation of a Bayesian CAD Modeler for Robotic Applications

We present a Bayesian CAD modeler for robotic applications. We address the problem of taking into account the propagation of geometric uncertainties when solving inverse geometric problems. The proposed method may be seen as a generalization of constraint-based approaches in which we explicitly model geometric uncertainties. Using our methodology, a geometric constraint is expressed as a probability distribution on the system parameters and the sensor measurements, instead of a simple equality or inequality. To solve geometric problems in this framework, we propose an original resolution method able to adapt to problem complexity. Using two examples, we show how to apply our approach by providing simulation results using our modeler

A Robotic CAD System using a Bayesian Framework

We present in this paper a Bayesian CAD system for robotic applications. We address the problem of the propagation of geometric uncertainties and how esian CAD system for robotic applications. We address the problem of the propagation of geometric uncertainties and how to take this propagation into account when solving inverse problems. We describe the methodology we use to represent and handle uncertainties using probability distributions on the system's parameters and sensor measurements. It may be seen as a generalization of constraint-based approaches where we express a constraint as a probability distribution instead of a simple equality or inequality. Appropriate numerical algorithms used to apply this methodology are also described. Using an example, we show how to apply our approach by providing simulation results using our CAD system

The Ariadne's Clew Algorithm

We present a new approach to path planning, called the ``Ariadne's clew algorithm''. It is designed to find paths in high-dimensional continuous spaces and applies to robots with many degrees of freedom in static, as well as dynamic environments --- ones where obstacles may move. The Ariadne's clew algorithm comprises two sub-algorithms, called SEARCH and EXPLORE, applied in an interleaved manner. EXPLORE builds a representation of the accessible space while SEARCH looks for the target. Both are posed as optimization problems. We describe a real implementation of the algorithm to plan paths for a six degrees of freedom arm in a dynamic environment where another six degrees of freedom arm is used as a moving obstacle. Experimental results show that a path is found in about one second without any pre-processing

Jet-driven outflows of ionized gas in the nearby radio galaxy 3C 293

Fast outflows of gas, driven by the interaction between the radio jets and interstellar medium (ISM) of the host galaxy, are being observed in an increasing number of galaxies. One such example is the nearby radio galaxy 3C 293. In this paper we present integral field unit observations taken with OASIS on the William Herschel Telescope, enabling us to map the spatial extent of the ionized gas outflows across the central regions of the galaxy. The jet-driven outflow in 3C 293 is detected along the inner radio lobes with a mass outflow rate ranging from ∼0.05 to 0.17 M yr−1 (in ionized gas) and corresponding kinetic power of ∼0.5– 3.5 × 1040 erg s−1. Investigating the kinematics of the gas surrounding the radio jets (i.e. not directly associated with the outflow), we find linewidths broader than 300 km s−1 up to 5 kpc in the radial direction from the nucleus (corresponding to 3.5 kpc in the direction perpendicular to the radio axis at maximum extent). Along the axis of the radio jet linewidths >400 km s−1 are detected out to 7 kpc from the nucleus and linewidths of >500 km s−1 at a distance of 12 kpc from the nucleus, indicating that the disturbed kinematics clearly extend well beyond the high surface brightness radio structures of the jets. This is suggestive of the cocoon structure seen in simulations of jet–ISM interaction and implies that the radio jets are capable of disturbing the gas throughout the central regions of the host galaxy in all directions

Autoimmune Responses in the Rheumatoid Synovium

Rene Toes and Tom Huizinga discuss a new study indicating that lymphoneogenesis in the inflamed synovial tissue of patients with rheumatoid arthritis is fostering potentially pathogenic immune responses

Palaeozoic Basement of the Pyrenees

International audienceIn the Pyrenees, the Cambrian-Lower Ordovician strata represent a quiescent time span with no remarkable tectonic activity, followed by a late Early-Mid Ordovician episode of uplift and erosion that led to the formation of the Sardic unconformity. Silurian sedimentation was widespread and transgressive followed by a Devonian succession characterized by a complex mosaic of sedi-mentary facies. Carboniferous pre-Variscan sediments (Tournaisian-Viséan cherts and limestones) precede the arrival of the synorogenic siliciclastic supplies of the Culm flysch at the Late Serpukhovian. All this succession was subsequently affected by the Serpukhovian-Bashkirian (Variscan) collision, as a result of which, the Palaeozoic rocks were incorporated into the northeastern branch of the Ibero-Armorican Arc