Robohub.org
 

ShanghAI Lectures: Tamim Asfour “Robots think with their hands”


by
13 March 2014



share this:

Tamim_AsfourGuest talk in the ShanghAI Lectures, 2010-12-16

The design of cognitive situated robots able to learn to operate in the real world and to interact and communicate with humans, must model and reflectively reason about their perceptions and actions in order to learn, act, predict and react appropriately. Such capabilities can only be attained by embodied agents through physical interaction with and exploration of the real world and requires the simultaneous consideration of perception and action. Representations built from such interactions are much better adapted to guiding behaviour than human crafted rules and allow embodied agents to gradually extend their cognitive horizon.

ShanghAI Lectures logoIn the first part of the talk, I present the concept of Object-Action Complexes (OAC, pronounced “oak”) which has been introduced by the European project PACO-PLUS (www.paco-plus.org) to emphasize the notion that objects and actions are inseparably intertwined and that categories are therefore determined (and also limited) by the action an agent can perform and by the attributes of the world it can perceive. Entities (things) in the world of a robot (or human) will only become semantically useful objects through the action that the agent can/will perform on them. The second part of the talk presents current results toward the implementation of integrated 24/7 humanoid robots able to 1) perform complex grasping and manipulation tasks in a kitchen environment 2) autonomously acquire object knowledge through visual and haptic exploration and 3) learn actions from human observation. The developed capabilities are demonstrated on the humanoid robots ARMAR-IIIa and ARMAR-IIIb.

https://www.youtube.com/watch?v=tJLzV418pF4

Slides

Tamim Asfour is senior research scientist and leader of the Humanoid Research Group at Humanoids and Intelligence Systems Lab, Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT).

His major research interest is humanoid robotics. In particular, his research topics include action learning from human observation, goal-directed imitation learning, dexterous grasping and manipulation, active vision and active touch, whole-body motion planning, cognitive control architectures, system integration, robot software and hardware control architecture, motor control and mechatronics.

He is leading the system integration tasks and the development team of the humanoid robot series ARMAR in the German Humanoid Robotics Project (SFB 588) funded by the German Research Foundation (DFG). He is currently involved in the following projects funded by the European Commission: PACO-PLUS, GRASP and Xperience.

Tamim Asfour is member of the Editorial Board of IEEE Transactions on Robotics and European Chair of the IEEE-RAS Technical Committee on Humanoid Robots. He is member the Executive Board of the German Association of Robotics (DGR: Deutsche Gesellschaft für Robotik). He serves as member on several program committees and review panels.

He received his diploma degree in Electrical Engineering (Dipl.-Ing.) in 1994 and his PhD in Computer Science (Dr.-Ing.) in 2003 from the University of Karlsruhe. In 2003 he was awarded with the Research Center for Information Technology (FZI) price for his outstanding Ph.D. thesis on sensorimotor control in humanoid robotics and the development of the humanoid robot ARMAR. Since September 2010 he holds an Adjunct Professor position at the Georgia Institute of Technology (Georgia Tech), College of Computing, Interactive Computing.

The ShanghAI Lectures are a videoconference-based lecture series on Embodied Intelligence, run and organized by Rolf Pfeifer (from 2009 till 2012), Fabio Bonsignorio (since 2013), and me with partners around the world. 

The ShanghAI Lectures have brought us a treasure trove of guest lectures by experts in robotics. You can find the whole series from 2012 here. Now, we’re bringing you the guest lectures you haven’t yet seen from previous years, starting with the first lectures from 2009 and releasing a new guest lecture every Thursday until all the series are complete. Enjoy!



tags: , ,


Nathan Labhart Co-organizing the ShanghAI Lectures since 2009.
Nathan Labhart Co-organizing the ShanghAI Lectures since 2009.





Related posts :



Interview with Kate Candon: Leveraging explicit and implicit feedback in human-robot interactions

and   25 Jul 2025
Hear from PhD student Kate about her work on human-robot interactions.

#RoboCup2025: social media round-up part 2

  24 Jul 2025
Find out what participants got up to during the second half of RoboCup2025 in Salvador, Brazil.

#RoboCup2025: social media round-up 1

  21 Jul 2025
Find out what participants got up to during the opening days of RoboCup2025 in Salvador, Brazil.

Livestream of RoboCup2025

  18 Jul 2025
Watch the competition live from Salvador!

Tackling the 3D Simulation League: an interview with Klaus Dorer and Stefan Glaser

and   15 Jul 2025
With RoboCup2025 starting today, we found out more about the 3D simulation league, and the new simulator they have in the works.

An interview with Nicolai Ommer: the RoboCupSoccer Small Size League

and   01 Jul 2025
We caught up with Nicolai to find out more about the Small Size League, how the auto referees work, and how teams use AI.

RoboCupRescue: an interview with Adam Jacoff

and   25 Jun 2025
Find out what's new in the RoboCupRescue League this year.

Robot Talk Episode 126 – Why are we building humanoid robots?

  20 Jun 2025
In this special live recording at Imperial College London, Claire chatted to Ben Russell, Maryam Banitalebi Dehkordi, and Petar Kormushev about humanoid robotics.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2025.05 - Association for the Understanding of Artificial Intelligence


 












©2025.05 - Association for the Understanding of Artificial Intelligence