Early reactive grasping with second order 3D feature relations

One of the main challenges in the field of robotics is to make robots ubiquitous. To intelligently interact with the world, such robots need to understand the environment and situations around them and react appropriately, they need context-awareness. But how to equip robots with capabilities of gathering and interpreting the necessary information for novel tasks through interaction with the environment and by providing some minimal knowledge in advance? This has been a longterm question and one of the main drives in the field of cognitive system development.

[1]  Antonio Morales,et al.  Heuristic vision-based computation of planar antipodal grasps on unknown objects , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[2]  Antonio Morales,et al.  Using Experience for Assessing Grasp Reliability , 2004, Int. J. Humanoid Robotics.

[3]  Michael Sorg,et al.  Visual determination of 3D grasping points on unknown objects with a binocular camera system , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[4]  Nancy S. Pollard,et al.  Closure and Quality Equivalence for Efficient Synthesis of Grasps from Examples , 2004, Int. J. Robotics Res..

[5]  Dan Ding,et al.  Computing 3-D optimal form-closure grasps , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[6]  Peter K. Allen,et al.  GraspIt!: A Versatile Simulator for Grasp Analysis , 2000, Dynamic Systems and Control: Volume 2.

[7]  Robert Platt,et al.  Extending fingertip grasping to whole body grasping , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[8]  Alexander Stoytchev,et al.  Behavior-Grounded Representation of Tool Affordances , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[9]  Jianwei Zhang,et al.  Visual guided grasping of aggregates using self-valuing learning , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[10]  Florentin Wörgötter,et al.  Multi-modal Primitives as Functional Models of Hyper-columns and Their Use for Contextual Integration , 2005, BVAI.

[11]  Shimon Edelman,et al.  Learning visually guided grasping: a test case in sensorimotor learning , 1998, IEEE Trans. Syst. Man Cybern. Part A.

[12]  Michael Felsberg,et al.  An explicit and compact coding of geometric and structural image information applied to stereo processing , 2004, Pattern Recognit. Lett..

[13]  Henrik I. Christensen,et al.  Automatic grasp planning using shape primitives , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[14]  Nancy S. Pollard,et al.  Parallel methods for synthesizing whole-hand grasps from generalized prototypes , 1994 .

[15]  Vijay Kumar,et al.  Robotic grasping and contact: a review , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[16]  Markus Lappe,et al.  Biologically Motivated Multi-modal Processing of Visual Primitives , 2003 .

[17]  Giulio Sandini,et al.  Learning about objects through action - initial steps towards artificial cognition , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[18]  Norbert Krüger,et al.  Three Dilemmas of Signal- and Symbol-Based Representations in Computer Vision , 2005, BVAI.

[19]  Florentin Wörgötter,et al.  Multi-modal Scene Reconstruction using Perceptual Grouping Constraints , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[20]  Tamim Asfour,et al.  Combining Appearance-based and Model-based Methods for Real-Time Object Recognition and 6D Localization , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  Martin Rutishauser,et al.  Searching for Grasping Opportunities on Unmodeled 3D Objects , 1995, BMVC.