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Planning and performing dynamic manipulations: Colloquium by Anton Shiriaev

Prof. Anton Shiriaeve from the Norwegian University of Science and Technology will visit the INI on November 16 and talk about his research about the planning and control of dynamic manipulations. 

His talk will take place at 14:00 in NB3/57. Here is an brief abstract of his talk: 

Abilities and skills in performing dynamic manipulations by humans appear in course of life-long training and experimentations. As a result, most of humans can readily manipulate or learn quickly how to manipulate external objects and environments without a firm grip or without re-grasping for re-orientating or moving. Here one can think of grasping and moving a wet soap when cleaning hands, of controlled rolling basketball ball on a palm in throwing it to the goal, think of manipulating knife in cutting soft materials etc. We can learn how to handle various objects or media for the purpose even them can slide or roll being in contact.

The talk is focused on challenging problems in modern robotics with emphasis of the discussion shifted to model-based approaches for developing some of human-like functionalities for robots. The intentions are examined by developing a solution for performing a rolling of passive objects (disc) on a robotic hand. Necessary mathematical concepts and arguments for the task are presented. Importance, relevance and scalability of the reasoning are supported by successful experimental studies on the robot


The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

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