Participants are invited to submit extended abstracts (2-4 pages) following the IEEE conference template. Send your pdf file to [hidden email] AND [hidden email].
Selected contributions will be presented during the workshop in a poster session.
Paper submission deadline: August 15, 2018
Notification of acceptance: September 5, 2018
Camera-ready version: September 15, 2018
Workshop: Friday 5 October 2018
Aim and Scope:
Humans display collaborative manipulation in many tasks, such as handovers and manipulation of objects excessively large and heavy for a lone person. Concurrently, robots are increasingly present in spaces shared with people where collaborative skills can complement human workers’ capabilities and increase efficiency, e.g., lifting heavy loads, working directly alongside humans with no safety caging, assisting humans in accomplishing complex and tedious tasks, combining the benefits of the fully manual assembly and fully automated manufacturing lines. To this end, forces, compliances, predictions and learning are critical for the success of cooperative manipulation and for the interaction to be safe. Many current projects are studying these key aspects in manipulation (e.g., H2020 CogIMon, H2020 SARAFun, H2020 Handy), confirming that robotic manipulation, particularly for shared tasks with humans, is a topic of high relevance nowadays and with deep resonance in the whole society (towards Industry 4.0).
During this workshop, we will focus on how to achieve safe and efficient human-robot collaboration in manipulation tasks and discuss key questions such as, what makes human collaboration so successful and how to transport and replicate it to robots, what is still missing in robotic manipulation to become optimally collaborative without separation and safety fencing, what the main approaches to collaborative manipulation are. Complementing humans sharing a workspace to accomplish a task more effectively involves challenges. The robot should be intuitive and safe through hardware and actions. Robots should recover and learn from errors. Based on a model of the task, the robot should coordinate its actions with its teammate’s actions within the model through communication (e.g., motion, speech). In addition, humans and robots can take different responsibilities such as: humans as supervisors providing information, instructions, decisions; humans and robots as peers working together at the same level to achieve a common goal; robots as assistants where humans lead.
We aim to bring together academic researchers and industrial experts in key areas for collaborative grasping and manipulation such as perception, control, learning, human studies and safety. We aspire to identify recent developments in these research areas, both in theory and applications, discussing recent achievements, debating underlying assumptions, and challenges for future progress.
1. Andrea M. Zanchettin, Politecnico Milano (Italy)
2. Sami Haddadin, Hannover University (Germany)
3. Anthony Remazeilles, Tecnalia (Spain)
4. Michael Mistry, University of Edinburgh (UK)
5. Sylvain Calinon, IDIAP/EPFL (CH)
6. Yukie Nagai, National Institute of Information and Communications Technology (NICT) (JP)
Topics of interest:
- Collaborative manipulation;
- Learning for manipulation;
- Human studies on grasping and manipulation;
- Bi-manual manipulation for human robot collaboration;
- Multimodal human-robot interaction for collaboration;
- Verbal, nonverbal, and co-verbal human-robot interaction for collaboration;
- Safe human-robot collaboration;
- Role of uncertainty in manipulation;
- Uncertainty in human-robot interaction.
- Intent reading and understanding;
- Role of force and compliance in collaborative tasks;
- Role of prediction in human and robotic manipulation.