In the near future robots will operate next to humans. Robots will be expected to know about all the objects in the domain where they are working. This will require methods to rapidly learn new objects, recognise and manipulate them. The talk will review recent advances such as learning objects from CAD models, learning object relations and parts, the use of semantic knowledge related to objects, and the detection of learned object classes from mobile robots.
Markus Vincze received his diploma in mechanical engineering from Technical University Wien (TUW) in 1988 and a M.Sc. from Rensselaer Polytechnic Institute, USA, 1990. He ﬁnished his PhD at TUW in 1993. With a grant from the Austrian Academy of Sciences he worked at HelpMate Robotics Inc. and at the Vision Laboratory of Gregory Hager at Yale University. In 2004, he obtained his habilitation in robotics. Presently he leads the Vision for Robotics (V4R) team at TUW with the vision to make robots see. V4R regularly coordinates EU (e.g., ActIPret, robots@home, HOBBIT) and national research projects (e.g, vision@home) and contributes to research (e.g., CogX, STRANDS, Squirrel, ALOOF) and innovation projects (e.g., Redux, FloBot). With Gregory Hager he edited a book on Robust Vision for IEEE and is (co-)author of 58 peer reviewed journal articles and over 400 reviewed other publications. He was the program chair of ICRA 2013 in Karlsruhe and will organize HRI 2017 in Vienna. Markus’ special interests are cognitive computer vision techniques for robotics solutions situated in real-world environments and especially homes. Personal website: www.acin.tuwien.ac.at/staff/vm/