[robotics-worldwide] [meetings] CFP: IROS 2018 Workshop - Towards Robots that Exhibit Manipulation Intelligence

Georg Bartels georg.bartels at cs.uni-bremen.de
Tue Jul 10 03:54:44 PDT 2018


Second Call for Papers

IROS 2018 Workshop - Towards Robots that Exhibit Manipulation Intelligence
October 1, 2018 (9am-5pm)
Madrid Municipal Conference Centre, Spain

Submission deadline: August 5th, 2018
Acceptance notification: August 24th, 2018

Contact and submission: iros18-manip-intel at cs.uni-bremen.de

*Call for Papers*
We are excited to announce the full-day workshop on Towards Robots that 
Exhibit Manipulation Intelligence. We invite authors to submit papers 
that they will present as spotlight talks (2-3min per paper), as well as 
during the interactive poster session (60min). The manuscripts shall use 
the standard IEEE IROS two-column format (2-4 pages). Manuscripts will 
be selected based on their originality, technical quality, clarity, and 
relevance to the topics of the workshop. Papers hosted on arXiv may be 
submitted, too.

We especially encourage women and young researchers to submit papers.

Please submit your manuscripts via e-mail to 
iros18-manip-intel at cs.uni-bremen.de

- Cognition­-enabled Robot Manipulation
- Learning and Adaptive Systems
- Manipulation Planning
- Mobile Manipulation
- Motion Control
- Perception for Grasping and Manipulation

*Important Dates*
- Submission: August 5, 2018
- Acceptance: August 24, 2018
- Camera-ready: September 7, 2018
- Workshop day: October 1, 2018

*Invited Speakers*
- Michael Beetz (Universität Bremen) -- confirmed
- Oussama Khatib (Stanford University) -- confirmed
- Alin Albu-Schäffer (DLR) -- confirmed
- Jeannette Bohg (Stanford University) -- confirmed
- Dieter Fox (University of Washington) -- confirmation pending
- Marc Toussaint (Universität Stuttgart) -- confirmed

The research field of mobile manipulation is at an exciting stage. 
Researchers have endowed robots with sophisticated motion capabilities. 
Those capabilities are the prerequisites for robots to perform 
real­-world actions like cooking meals, assembling products, helping 
dress people, or doing laundry. However, there are still many open 
research questions. For instance, the robot control systems providing 
those motion capabilities typically have to be parameterized with 
action­ and context­-specific mathematical models. Unfortunately, it is 
still an open question how to autonomously translate a given 
manipulation problem and a perceived geometric scene into a meaningful 
mathematical model for motion generation. As a result, endowing a robot 
with a new manipulation skill or transferring a skill to a new context 
requires human creative input. To overcome this bottleneck in the 
development of mobile manipulation applications, robots need 
'manipulation intelligence.'

Manipulation intelligence refers to the ability to understand the 
interplay of motions and effects. To clarify this description, let us 
consider the instructive example of a robot that shall flip a pancake 
with a spatula. A robot with manipulation intelligence knows that 
pancakes can break or fold during the flipping. This knowledge allows 
the creation of an automated feedback loop: Before performing an 
intended motion, the robot can predict probable effects on the pancake. 
If those are problematic, e.g. because one particular pancake appears to 
be unusually thin, the robot can modify the motion– without the need for 
human intervention. During and after flipping, the robot can monitor 
what happens to the pancake and trigger motion adaptation, if unwanted 
effects like folding occur or the robot failed to flip the pancake.

Research on this new generation of robot control systems has already 
started. As a result, the development of robotic applications will be 
faster and easier, enabling projects of much grander scale and ambition 
than the robotics community can tackle today. The resulting robots will 
possess better abilities to learn new actions and perform known actions 
in new contexts.

This workshop aims to bring together researchers that are fascinated and 
driven by the question of how to build this next generation of robot 
control systems. Specifically, we invite researchers working on robot 
control, machine learning, task and motion planning, and 
knowledge-­based robotics who try to combine these technologies. The 
main objectives of this workshop are to formulate key research 
questions, identify potential synergies, and outline a road map for 
young researchers towards robots that exhibit manipulation intelligence.

- Michael Beetz (Universität Bremen)
- Georg Bartels (Universität Bremen)
- Marc Toussaint (Universität Stuttgart)
- Alin Albu-Schäffer (DLR)
- Oussama Khatib (Stanford University)

Georg Bartels          | georg.bartels at cs.uni-bremen.de
Universität Bremen     | Am Fallturm 1
28359 Bremen           | Germany
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