Project Details
Projekt
Autonomous Active Object Learning Through Robot Manipulation
Subject Area
Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
Term
from 2014 to 2019
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 260307391
Service robots have the potential to be ubiquitous helpers of our everyday life. They are envisioned to perform a variety of tasks ranging from cleaning our apartments to mowing our lawn or feeding our pets. For solving such tasks successfully, robots must be able to properly reason about and manipulate objects, which requires rich knowledge about the corresponding objects. To obtain such knowledge, robots need not only means for analyzing the geometry and appearance of objects but also for retrieving their categories and inferring their characteristics. This includes, for example, physical properties such as material and weight, or parts and their functions, as well as other forms of information such as object brand or price. In this project, we aim at learning all the object information with minimal human supervision by leveraging the possibility of physical object interaction and by analyzing the information available in the World Wide Web. Furthermore, we aim at the transfer of manipulation skills from a generic model to the specific shape and characteristics of novel objects and the autonomous improvement of these.For our research, we will use state-of-the-art robots equipped with manipulator We propose a novel active learning perspective. s. We provide the robot with prior knowledge about objects and give the robot access to the information available on the web that is continually updated and with large diversity. The robot actively learns by testing the estimated hypotheses through interaction with the environment, e.g., by taking object data, pushing or picking an object. It learns novel skills for manipulating the objects from demonstrations, which it generalizes to functionally similar objects and improves from experience with these. ALROMA will advance the state of the art in active and robot learning, object manipulation and object discovery and will contribute to the next generation of service robots.
DFG Programme
Priority Programmes
Subproject of
SPP 1527:
Autonomous Learning
Participating Person
Dr. Luciano Spinello
