Vorläufige Themenliste

Task Space Control with Redundancy Resolution

• Comparative Experiments on Task Space Control with Redundancy Resolution (Jun Nakanishi, Rick Cory, Michael Mistry, Jan Peters, and Stefan Schaal), IROS 2005. [pdf]

Task Function Approach

• iTaSC: A tool for multi-sensor integration in robot manipulation (Ruben Smits, Tinne De Laet, Kasper Claes, Herman Bruyninckx, Joris De Schutter), IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems 2008 [pdf]

A longer and more detailed description of the approach for 2nd reading:

• Constraint-based task specification and estimation for sensor-based robot systems in the presence of geometric uncertainty (Joris De Schutter, Tinne De Laet, Johan Rutgeerts, Wilm Decŕe, Ruben Smits, Erwin Aertbelien, Kasper Claes and Herman Bruyninckx), The International Journal of Robotics Research May 2007 [pdf]

Imitation Learning

• Learning Stable Non-Linear Dynamical Systems with Gaussian Mixture Models (Khansari-Zadeh, Seyed Mohammad; Billard, Aude), IEEE Transaction on Robotics, vol. 27, num. 5, 2011. [pdf]

Grasping

• Contact-reactive grasping of objects with partial shape information (Kaijen Hsiao, Sachin Chitta, Matei Ciocarlie, and E. Gil Jones), IROS 2010. [pdf]

Application of the above system that should also be considered in detail:

• Human-Inspired Robotic Grasp Control With Tactile Sensing (Joseph M. Romano, Kaijen Hsiao, Günter Niemeyer, Sachin Chitta, and Katherine J. Kuchenbecker), IEEE Transactions on Robotics, 2011, Issue 6, Volume 27.

Motion Planning

• CHOMP: Gradient optimization techniques for efficient motion planning (Nathan Ratliff, Matt Zucker, J. Andrew Bagnell, and Siddhartha Srinivasa), ICRA 2009. [pdf]

• STOMP: Stochastic trajectory optimization for motion planning (Kalakrishnan, M.;Chitta, S.;Theodorou, E.;Pastor, P.;Schaal, S.), ICRA 2011. [pdf]

World Modelling

• OctoMap: An Efficient Probabilistic 3D Mapping Framework Based on Octrees (Armin Hornung, Kai M. Wurm, Maren Bennewitz, Cyrill Stachniss, and Wolfram Burgard), Autonomous Robots, 2013. [pdf]

General Overview

• Vision for Robotics, Markus Vincze and Danica Kragic in Foundations and Trends in Robotics Vol. 1, No. 1 (2010) 1–78 [pdf]

Point Cloud perception

• 3D is here: Point Cloud Library (PCL) , Rusu, R.B.;Cousins, S., Robotics and Automation (ICRA), 2011 IEEE International [pdf]
• Tutorial: Point Cloud Library: Three-Dimensional Object Recognition and 6 DOF Pose Estimation, Aldoma, A.;Marton, Zoltan-Csaba; Tombari, F.; Wohlkinger, W.; Potthast, C.; Zeisl, B.; Rusu, R.B.; Gedikli, S.; Vincze, M. in Robotics & Automation Magazine, IEEE , Volume: 19 , Issue: 3 Page(s): 80 - 91 [pdf]

Object Recognition

• A Scalable Tree-based Approach for Joint Object and Pose Recognition, K. Lai, L. Bo, X. Ren, D. Fox Robotics and Automation (ICRA), 2011 IEEE International [pdf]

• Segmentation of Unknown Objects in Indoor Environments, A. Richtsfeld, T. Mörwald, J. Prankl, M. Zillich and M. Vincze, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012 [pdf]

• Object recognition in 3D scenes with occlusions and clutter by Hough voting F. Tombardi and L. Di Stefano, 2010 Fourth Pacific-Rim Symposium on Image and Video Technology [pdf]

SLAM

• An Evaluation of the RGB-D SLAM System, Felix Endres,Jürgen Sturm,Jürgen Hess,Daniel Cremers,Nikolas Engelhard,Wolfram Burgard, Robotics and Automation (ICRA), 2012 IEEE International [pdf]

Robot Vision Systems

• ROBOSHERLOCK: Unstructured Information Processing for Robot Perception, submited to RSS2013, paper in print on request.

• Exploiting Domain Knowledge for Object Discovery, Alvaro Collet Romea, Bo Xiong, Corina Gurau, Martial Hebert, and Siddhartha Srinivasa, IEEE International Conference on Robotics and Automation (ICRA), May, 2013. [pdf]

• The MOPED framework: Object Recognition and Pose Estimation for Manipulation Alvaro Collet, Manuel Martinez, Siddhartha Srinivasa, The International Journal of Robotics Research (IJRR), April, 2011 [pdf]

Reasoning-Based Plan Execution

• Knowledge Enabled High-Level Task Abstraction and Execution. J. Winkler, G. Bartels, L. Mösenlechner, M. Beetz. 2012. [pdf]
• Parameterizing Actions to have the Appropriate Effects. L. Mösenlechner, M. Beetz. 2011. [pdf]

Robot Plan Languages

• Plan Representations for Picking Up Trash. R. J. Firby, P. Prokopowicz, M. Swain. 1995. [pdf]
• Universal plans for reactive robots in unpredictable environments. M. J. Schoppers. 1987. [pdf]
• PRS: A high level supervision and control language for autonomous mobile robots. F. F. Ingrand, R. Chatila, R. Alami, F. Robert. 1996.

Object-Handling using Semantic Object Characteristics

• Robotic grasping of novel objects using vision. A. Saxena, L. Driemeyer, A. Y. Ng. 2008. [pdf]
• Semantic Grasping: Planning Robotic Grasps Functionally Suitable for An Object Manipulation Task. H. Dang, P. K. Allen. 2012. [pfd]
• Automatic Grasp Planning Using Shape Primitives. A. T. Miller, S. K. Henrik I. Christensen, P. K. Allen. [pdf]

Plan Execution in Highly Dynamic Environments

• Plan Execution Monitoring and Control Architecture for Mobile Robots. F. R. Noreils, R. G. Chatila. 1995.
• Towards Performing Everyday Manipulation Activities. M. Beetz, D. Jain, L. Mösenlechner. 2010. [pdf]

Planning for Human-Robot Interaction

• An Integrated Planning and Learning Framework for Human-Robot Interaction. A. Kirsch, T. Krause, L. Mösenlechner. 2009. [pdf]
• Task planning for Human-Robot Interaction. R. Alami, A. Clodic, V. Montreuil, E. A. Sisbot, R. Chatila. 2005. [pdf]

Description Logics

• Beschreibungslogik als Repräsentationssprache: Grundlegende Konzepte, Mächtigkeit, Limitierungen. Baader, Franz, Ian Horrocks, and Ulrike Sattler. “Description logics.” Foundations of Artificial Intelligence 3 (2008): 135-179.[pdf]
• Grounding und Anchoring von Wissen: Wie kann man die abstrakten Symbole der Wissensbasis in der realen Welt finden und wiederfinden? Harnad, Coradeschi

OWL and Semantic Web

• Wissensdarstellung im Semantic Web: Welche Sprachen und Konzepte werden im Semantic Web verwendet, einer web-basierten, verteilten Wissensbasis? Semantic Web OWL, Semantic Web services, Semantic Web language stack (XML, RDF, RDFS, OWL)
• Wissensextraktion aus Internet-Quellen: Wie kann man aus bestehenden Internet-Daten Wissen extrahieren und zur automatischen Inferenz nutzen? Textrunner, CMU Read The Web

Knowledge representation and reasoning for robots

• Wissensbasierte Roboter-Steuerung: Wie kann Wissen so darstellen, dass ein Roboter es für seine Aufgaben verwenden kann? KnowRob, ORO, OUR-K, Grounded Situation Models

Cloud robotics

• Cloud Robotics and Automation: A Survey of Related Work. K. Goldberg and B. Kehoe. EECS Department, University of California, Berkeley, Technical Report UCB/EECS-2013-5. January 2013. [pdf]
• Markus Waibel, Michael Beetz, Raffaello D'Andrea, Rob Janssen, Moritz Tenorth, Javier Civera, Jos Elfring, Dorian Gálvez-López, Kai Häussermann, J.M.M. Montiel, Alexander Perzylo, Björn Schießle, Oliver Zweigle, René van de Molengraft, “RoboEarth - A World Wide Web for Robots”, In Robotics & Automation Magazine, IEEE, vol. 18, no. 2, pp. 69-82, 2011. [pdf]

Using information from the Web for robots

• Web-enabled Robots – Robots that Use the Web as an Information Resource (Moritz Tenorth, Ulrich Klank, Dejan Pangercic, Michael Beetz), In Robotics & Automation Magazine, IEEE, volume 18, 2011. [pdf]