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  <title>E-Archivo Community:</title>
  <link rel="alternate" href="http://hdl.handle.net/10016/6473" />
  <subtitle />
  <id>http://hdl.handle.net/10016/6473</id>
  <updated>2013-05-20T06:16:07Z</updated>
  <dc:date>2013-05-20T06:16:07Z</dc:date>
  <entry>
    <title>Context-Aided Sensor Fusion for Enhanced Urban Navigation</title>
    <link rel="alternate" href="http://hdl.handle.net/10016/16248" />
    <author>
      <name>Martí, Enrique David</name>
    </author>
    <author>
      <name>Martin, David</name>
    </author>
    <author>
      <name>García, Jesús</name>
    </author>
    <author>
      <name>Escalera, Arturo de la</name>
    </author>
    <author>
      <name>Molina, José M.</name>
    </author>
    <author>
      <name>Armingol, José M.</name>
    </author>
    <id>http://hdl.handle.net/10016/16248</id>
    <updated>2013-02-20T12:47:42Z</updated>
    <published>2012-11-30T23:00:00Z</published>
    <summary type="text">Title: Context-Aided Sensor Fusion for Enhanced Urban Navigation
Author(s): Martí, Enrique David; Martin, David; García, Jesús; Escalera, Arturo de la; Molina, José M.; Armingol, José M.
Abstract: The deployment of Intelligent Vehicles in urban environments requires reliable estimation of positioning for urban navigation. The inherent complexity of this kind of environments fosters the development of novel systems which should provide reliable and precise solutions to the vehicle. This article details an advanced GNSS/IMU fusion system based on a context-aided Unscented Kalman filter for navigation in urban conditions. The constrained non-linear filter is here conditioned by a contextual knowledge module which reasons about sensor quality and driving context in order to adapt it to the situation, while at the same time it carries out a continuous estimation and correction of INS drift errors. An exhaustive analysis has been carried out with available data in order to characterize the behavior of available sensors and take it into account in the developed solution. The performance is then analyzed with an extensive dataset containing representative situations. The proposed solution suits the use of fusion algorithms for deploying Intelligent Transport Systems in urban environments.</summary>
    <dc:date>2012-11-30T23:00:00Z</dc:date>
  </entry>
  <entry>
    <title>A new finger inverse kinematics method for an anthropomorphic hand</title>
    <link rel="alternate" href="http://hdl.handle.net/10016/14116" />
    <author>
      <name>Bensalah, Choukri</name>
    </author>
    <author>
      <name>Abderrahim, Mohamed</name>
    </author>
    <author>
      <name>González Gómez, Juan</name>
    </author>
    <id>http://hdl.handle.net/10016/14116</id>
    <updated>2012-06-08T10:42:06Z</updated>
    <published>2010-12-31T23:00:00Z</published>
    <summary type="text">Title: A new finger inverse kinematics method for an anthropomorphic hand
Author(s): Bensalah, Choukri; Abderrahim, Mohamed; González Gómez, Juan
Abstract: In this paper, a new method for solving the inverse kinematics of the fingers of an anthropomorphic hand is proposed. Our approach combines a Modified Selectively Damped Least Squares (MSDLS) and Jacobian Transpose (JT) methods. The main advantages of this method with respect to the ordinary SDLS are: optimal Cartesian increment, shorter computation time and better response near singularity configurations. The original JT method exhibits a strong shattering with small magnitudes which occurs near the goal position or in the case of unreachable positions. Like in the SDLS, a damping factor was applied to each input singular vector to filter the undesirable behavior. A comparative study between the MSDLS applied to the inverse Jacobian and JT matrix is developed to investigate manipulator performance in critical end-point positions of the index finger of a commercial anthropomorphic robotic hand and also to evaluate the impact of the increment length on computation time.
Description: Proceedings of: 2011 IEEE International Conference on Robotics and Biomimetics (ROBIO), December 7-11, 2011, Phuket (Thailand)</summary>
    <dc:date>2010-12-31T23:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Adaptive sensor-fusion of depth and color information for cognitive robotics</title>
    <link rel="alternate" href="http://hdl.handle.net/10016/14114" />
    <author>
      <name>Klimentjew, Denis</name>
    </author>
    <author>
      <name>Zhang, Jianwei</name>
    </author>
    <id>http://hdl.handle.net/10016/14114</id>
    <updated>2012-06-08T09:30:46Z</updated>
    <published>2010-12-31T23:00:00Z</published>
    <summary type="text">Title: Adaptive sensor-fusion of depth and color information for cognitive robotics
Author(s): Klimentjew, Denis; Zhang, Jianwei
Abstract: The presented work goes one step further than only combining data from different sensors. The corresponding points of an image and a 3D point cloud are determined through calibration. Color information is thereby assigned to every voxel in the overlapping area of a stereo camera system and a laser range finder. Then we analyze the image and search for the locations, which are especially susceptible to errors by both sensors. Depending on the ascertained situation, we try to correct or minimize errors. By analyzing and interpreting the images as well as removing errors we create an adaptive tool which improves multi-sensor fusion. This allows us to correct the fused data and to perfect the multi-modal sensor fusion or to predict the locations where the sensor information is vague or defective. The presented results demonstrate a clear improvement over standard procedures and show that other progress based on our work is possible.
Description: Proceedings of: 2011 IEEE International Conference on Robotics and Biomimetics (ROBIO), December 7-11, 2011, Phuket (Thailand)</summary>
    <dc:date>2010-12-31T23:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Programming-by-demonstration and adaptation of robot skills by fuzzy-time-modeling</title>
    <link rel="alternate" href="http://hdl.handle.net/10016/13982" />
    <author>
      <name>Palm, Rainer</name>
    </author>
    <author>
      <name>Iliev, Boyko</name>
    </author>
    <id>http://hdl.handle.net/10016/13982</id>
    <updated>2012-06-11T07:43:47Z</updated>
    <published>2011-06-30T22:00:00Z</published>
    <summary type="text">Title: Programming-by-demonstration and adaptation of robot skills by fuzzy-time-modeling
Author(s): Palm, Rainer; Iliev, Boyko
Abstract: Complex robot tasks can be partitioned into motion primitives or robot skills that can directly be learned and recognized through Programming-by-Demonstration (PbD) by a human operator who demonstrates a set of reference skills. Robot motions are recorded by a data-capturing system and modeled by a specific fuzzy clustering and modeling technique where skill models use time instants as inputs and operator actions as outputs. In the recognition phase the robot identifies the skill shown by the operator in a novel test demonstration. Skill models are updated online during the execution of skills using the Broyden update formula. This method is extended for fuzzy models especially for time cluster models. The updated model is used for further executions of the same skill.
Description: Proceedings of: 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiS 2011 MDCM), April 11-15, 2011, Paris (France)</summary>
    <dc:date>2011-06-30T22:00:00Z</dc:date>
  </entry>
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