Research seminar "Robots that act and interact"

Abstract

The ability to autonomously acquire new knowledge through interaction with the environment is an important ability of any intelligent system. The knowledge can be acquired only if suitable perception-action capabilities are present. A robotic system has to be able to detect, attend to and manipulate objects in the environment. This talk presents some of the most important challenges and some of the results of our longterm work in the area of vision based sensing and control. The work on finding, attending, recognizing and manipulating objects in domestic environments is discussed. We also present our work on the visual analysis of human manipulation actions which are of interest for e.g. human-robot interaction applications where a robot learns how to perform a task by watching a human. A method for classifying manipulation actions in the context of the objects manipulated, and classifying objects in the context of the actions used to manipulate them is presented.

Speaker biography

Danica Kragić is a Professor at the School of Computer Science and Communication at KTH in Stockholm. She received MSc in Mechanical Engineering from the Technical University of Rijeka, Croatia in 1995 and PhD in Computer Science from KTH in 2001. She has been a visiting researcher at Columbia University, Johns Hopkins University and INRIA Rennes. She is the Director of the Centre for Autonomous Systems at KTH and the coordinator for the EC integrated project GRASP and TOMSY. Danica is a member of the Royal Swedish Aacdemy of Sciences and Young Academy of Sweden.

Danica received the 2007 IEEE Robotics and Automation Society Early Academic Career Award. She is charing the IEEE RAS Technical Committee on Computer and Robot Vision and from 2009 serves as an IEEE RAS AdCom member. Her research is in the area of computer vision, object grasping and manipulation and human-robot interaction. In the area of computer vision she is interested in developmnet of active vision systems allowing robots to interact with humans and each others in realistic environments. Her recent work explores different learning methods for formalizing the models for integrated representation of objects and actions that can be applied on them. This work has demonstrated how robots can achieve scene understanding through active exploration and how full body tracking of humans can be made more efficient.