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Modelling Primate Control of Grasping for Robotics Applications

  • Ashley KleinhansEmail author
  • Serge Thill
  • Benjamin Rosman
  • Renaud Detry
  • Bryan Tripp
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8926)

Abstract

The neural circuits that control grasping and perform related visual processing have been studied extensively in macaque monkeys. We are developing a computational model of this system, in order to better understand its function, and to explore applications to robotics. We recently modelled the neural representation of three-dimensional object shapes, and are currently extending the model to produce hand postures so that it can be tested on a robot. To train the extended model, we are developing a large database of object shapes and corresponding feasible grasps. Finally, further extensions are needed to account for the influence of higher-level goals on hand posture. This is essential because often the same object must be grasped in different ways for different purposes. The present paper focuses on a method of incorporating such higher-level goals. A proof-of-concept exhibits several important behaviours, such as choosing from multiple approaches to the same goal. Finally, we discuss a neural representation of objects that supports fast searching for analogous objects.

Keywords

Grasping Affordances Macaque Robotics AIP F5 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ashley Kleinhans
    • 1
    Email author
  • Serge Thill
    • 2
  • Benjamin Rosman
    • 1
  • Renaud Detry
    • 3
  • Bryan Tripp
    • 4
  1. 1.CSIRPretoriaSouth Africa
  2. 2.University of SkövdeSkövdeSweden
  3. 3.University of LiègeLiègeBelgium
  4. 4.University of WaterlooWaterlooCanada

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