Artificial Intelligence for Human-Robot Interaction

• Applicant: Professor Dr. Michael Beetz, Ph.D.
• Subject Area: Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics ; Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 442588247

Europe and Japan both face problems of shrinking and aging population. This raises a number of issues like missing workforce, and robots are often seen as a possible way for alleviating them. However, that would require that robots are introduced into human societies and work in direct contact with people.The field of Human-Robot Interaction (HRI) is concerned with the ways in which robots should interact with people in the social world. But dealing with humans is notoriously difficult and represents a huge challenge. At the same time, there are many successful applications of Artificial Intelligence techniques to increasingly complex tasks. Regardless of that, the field of HRI has largely not yet taken benefit from advanced AI techniques. Conversely, HRI can be considered as a very motivating challenge for AI, where the human is physically and mentally in the loop. The goal of the AI4HRI project will be to both develop and tightly integrate several crucial AI technologies that will allow social robots to appropriately and skillfully deal with humans around them. HRI is currently missing sophisticated knowledge management methods and models, as well as knowledge reasoning abilities that can be used by a robot interacting with humans. What we are interested in: is what needs to be implemented successfully in the knowledge management system, which kind of models of the humans the robot should build, and which kind of reasoning abilities the robot should have regarding itself and the human it interacts with. Building upon this knowledge, we will study how a robot needs to socially interact with a human. Explicit manual programming of the interaction behaviors that the robot should execute is often done in HRI, but it is very difficult to create interactions that are robust to all variations of environment or human behavior. Therefore we will use machine learning techniques to learn the interaction patterns that humans use in interactions with other humans and copy them to a human-robot interaction context. The AI4HRI project brings together three teams from LAAS (France), University of Bremen (Germany), and Kyoto University (Japan), who are not only world leaders in AI or HRI, but who also have very complementary approaches to solving the issues addressed by the project. Through their synergies, we will be able to develop the integrated open-source architecture described above, which is something that could not have been possible by any of the teams alone. The goal will be achieved through continuous collaboration and meetings of the involved researchers. We are confident that the result of this project will become an important milestone for achieving a future with socially interactive robots working in close vicinity to us.

• DFG Programme: Research Grants
• International Connection: France, Japan
• Partner Organisation: Agence Nationale de la Recherche / The French National Research Agency; Japan Science and Technology Agency; JST
• Cooperation Partners: Dr. Aurélie Clodic; Dr. Takayuki Kanda