Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

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Session WedFVT9 Fenix 1 Wednesday, October 10, 2012, 16:15–17:30 Multi-modal Learning II Chair Co-Chair Shingo Shimoda, RIKEN 16:15–16:30 WedFVT9.1 Experimental study on haptic communication of a human in a shared human-robot collaborative task Julie Dumora, Franck Geffard, Catherine Bidard LIST, CEA, France Thibaut Brouillet Philippe Fraisse EPSYLON, Montpellier, France LIRMM, Montpellier, France • Robot assistances and operator intention detection proposed to overcome limitations of backdrivable robot in long objects manipulation • The solution of analysing haptic cues to tackle the rotation/translation ambiguity is proposed • Relationships between operator intention of motion and haptic measurements are highlighted • Wrench measurements are shown to be an incomplete information for detection of operator’s intention of motion Rotation/translation ambiguity in joint human-robot manipulation of a long object (view from top down) 16:45–17:00 WedFVT9.3 Maximally Informative Interaction Learning for Scene Exploration Herke van Hoof, Oliver Kroemer, Heni Ben Amor and Jan Peters FG Intelligent Autonomous Systems, TU Darmstadt, Germany Max Planck Institute for Intelligent Systems, Germany • In dynamic environments, robots need to handle novel objects. • As annotated data is absent robots need to learn from the results of their actions. • Exploratory actions that maximize information gain allow more efficient learning. • This method allows a robot to efficiently learn with minimal prior information. 17:15–17:20 WedFVT9.5 Towards Robotic Calligraphy Nico Huebel, Elias Mueggler, Markus Waibel, and Raffaello D’Andrea Institute for Dynamic Systems and Control, ETH Zurich, Switzerland • We present a prototype of a robotic system that learns how to draw Chinese characters. • First, the context of the project is presented. • Then, the experimental setup and the overall approach is introduced. • Finally, experimental results are presented and discussed. This is the experimental setup of our prototype consisting of the KUKA Light Weight Robot, a Prosilica GC 655C camera, and a brush. 16:30–16:45 WedFVT9.2 Robots Move: Bootstrapping the Development of Object Representations using Sensorimotor Coordination Arren Glover and Gordon Wyeth Queensland University of Technology, Australia • This paper is concerned with the unsupervised generation of object models by fusing appearance and action • A FAB-MAP-based approach is combined with a partially observable semi-Markov decision process • Results indicate stronger bag-ofword object representations are formed under sensorimotor constraints 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems –182– Representations are matched via self-motion prediction to become object specific 17:00–17:15 WedFVT9.4 Perceptual Development Triggered by its Self-Organization in Cognitive Learning Yuji Kawai, Yukie Nagai, and Minoru Asada Graduate School of Engineering, Osaka University, Japan • Our goal: To investigate the role of visual development triggered by selforganization in the visual space in a case of the mirror neuron system (MNS) • Key idea: The self-triggered visual development changes adaptively the developmental speed. • Result: The self-triggered development maintains a long enough period of immature vision which can inhibit selfother differences in observation. Thus the development enhances the acquisition of the association between self and other (i.e., the MNS). (a) Early stage of development (b) Later stage of development 17:20–17:25 WedFVT9.6 Learning Throwing and Catching Skills Jens Kober, Katharina Muelling, and Jan Peters AGBS, MPI for Intelligent Systems, Germany IAS, TU Darmstdat, Germany • Learning hitting skills by imitation and reinforcement learning • Generalizing hitting skills to catching skills • Learning to throw at targets • Combining throwing and catching skills to play catch A BioRob and a Barrett WAM playing catch.
Session WedFVT9 Fenix 1 Wednesday, October 10, 2012, 16:15–17:30 Multi-modal Learning II Chair Co-Chair Shingo Shimoda, RIKEN 17:25–17:30 WedFVT9.7 NAO Walking Down a Ramp Autonomously Christian Lutz, Felix Atmanspacher, Armin Hornung, and Maren Bennewitz Dept. of Computer Science, University of Freiburg, Germany • We present a method to traverse ramps with humanoids using onboard vision and IMU sensors • Our NAO humanoid autonomously walks down a steep ramp of 2 m • Single statically stable steps on the ramp are learned with kinesthetic teaching • Start and end of the ramp are detected from straight lines in the camera image • The robot‘s orientation is inferred from the ramp inclination with roll and pitch angles of the IMU NAO on the ramp (top) and on-board camera images with detected lines (bottom) 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems –183–
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Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

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