International Journal of Social Robotics - Call for Papers: Special Issue on Knowledge, Learning, Planning, and Human Behavior Modeling for Autonomous Social Robots
Guest Editors:
Ely Repiso Polo, LAAS-CNRS, France
Malcolm Doering, Kyoto University, Japan
Aurélie Clodic, LAAS-CNRS, France
Guillaume Sarthou, Institute for Artificial Intelligence, Germany
Rachid Alami, LAAS-CNRS, France
Dražen Brščić, Kyoto University, Japan
Takayuki Kanda, Kyoto University, Japan
Mona Abdel-Keream, Institute for Artificial Intelligence, Germany
Michael Beetz, Institute for Artificial Intelligence, Germany
Submission deadline: June 15, 2024
Description
Nowadays, with the advance of artificial intelligence (AI) and other methods in robotics, there is a growing move to use AI-enabled “intelligent algorithms” in robots for human-robot interaction to perform a wide range of diverse tasks combining the best abilities of humans and robots to achieve success. AI includes all these sub-fields of research: knowledge modeling and reasoning, learning, planning and decision-making, and human behavior modeling for autonomous social robots. The problem is that social interaction is complex as it depends not only on physical but also on a multitude of psychological, sociological, and other factors. This makes reasoning and learning about social interaction incredibly challenging. Therefore, nowadays most Human-Robot Interaction (HRI) researchers are improving their methods with more advanced techniques or creating collaborations between them to get complex behaviours that cover different research fields.
This special issue will cover topics ranging from methodologies and techniques for solving focused, concrete aspects of these types of human-robot interaction to more complex and general approaches of HRI that combine multiple different techniques into a larger system. This special issue comes from the IROS2022 workshop (this opens in a new tab) and the Artificial Intelligence for Human-Robot Interaction (this opens in a new tab) trilateral project lead from LAAS, CNRS, France by Aurélie Clodic and Rachid Alami; HRI Lab., Kyoto University, Japan by Takayuki Kanda; and IAI, Bremen University, Germany by Michael Beetz. The goal of the AI4HRI project is to combine joint action planning and execution, social interaction learning, and knowledge reasoning and representation into a unified architecture for human-robot interaction. In this way, more intelligent robot behaviors for human-robot collaboration to accomplish joint goals can be achieved. Therefore, we will accept papers from various areas related to AI for HRI, embedded in social robots or realistic simulations of them. The general topic of this special issue is knowledge, learning, planning, and human behavior modeling for autonomous social robots Interacting with humans in any type of environment (realistic simulation, laboratories, and field studies) using various methods. These interactions can be between single or multiple humans and robots, and short or long term HRI. The workshop subtopics include, but are not limited to:
· Human-Robot joint action planning and execution
· Supervision systems and error management for HRI
· Detection or use of human social practices for HRI (including context, engagement, commitments, joint attention, social rules for interaction, spatial perspective taking, social cues, etc.)
· Knowledge representation and reasoning for HRI (including ontologies and other knowledge representations.)
· Human Behavior Modeling for HRI
· Modeling the human's perspective for HRI
· Learning of social interaction behaviors for HRI (for example, imitation learning from examples of human social interaction)
· Evaluation of the quality of the autonomous collaboration between robot and human, which is applicable to robots that use Artificial Intelligence methods (previous subtopics)
· Human-robot collaboration models for autonomous “intelligent” social robots
· Realistic simulation systems for collaborative HRI (Using Unreal, ROS-Gazebo, or similar), for example, to simulate either humans or robots
· Autonomous human-like social communication (including speech and/or gestures) to facilitate or enhance the robot's "intelligent" behavior
· Any human-like intelligent behavior and cognition for autonomous social robots (in lab/real/virtual environments)
How to submit your article
All submissions must be original and may not be under review by another publication. Interested authors should consult the journal’s “Submission Guidelines” (this opens in a new tab) at https://www.springer.com/journal/12369/submission-guidelines (this opens in a new tab)
Articles can be submitted through Editorial Manager (this opens in a new tab): https://www.editorialmanager.com/soro/default.aspx (this opens in a new tab)
The special issue is created as submission questionnaire in the system. When you submit your paper you will be asked if your paper belongs to a special issue. Please answer yes, and then select “SI Knowledge, Learning, Planning, and Human Behavior Modeling for Autonomous Social Robots” from the pull-down menu.
All submitted papers will be reviewed on a peer review basis as soon as they are received. Accepted papers will become immediately available Online First until the complete Special Issue appears.
Guest Editor Biographies
Ely Repiso is a Post PhD researcher related to the trilateral project of Artificial Intelligence for Human Robot Interaction (AI4HRI) at LAAS-CNRS of Toulouse, France. She received her Ph.D. in Collaborative Social Robot Navigation in Accompanying and Approaching Tasks from the Doctorat en Automàtica, Robòtica i Visió (ARV) of the Universitat Politècnica de Catalunya (UPC) in 2020, with international mention and the qualification Excellent Cum Laude. During her Ph.D., she did a research stay at the ATR of Japan under the supervision of Takayuki Kanda, and she participates with her Ph.D.-work in several national and international projects related to the Institut of Robotica e Informatica Industrial (IRI) (Cargo-ANTS, ColRobTransp, Robot-Int-Coop, ROBOCOM++, TERRINET, AI4EU, MdM). She was an assistant professor at the UPC during the academic courses of 2019/2020 and 2020/2021. Her research interests include people-tracking, people prediction, robot navigation, robot-human accompaniment, robot approaching to people, task planning for Human robot Interaction, and general HRI.
Malcolm Doering is a Specially-Appointed Assistant Professor at the Human-Robot Interaction Laboratory, Kyoto University; and Cooperative Researcher at Interaction Science Laboratories, Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan. His research focuses on data-driven imitation learning methods for human-robot interaction. More specifically, he researches how robots can learn interactive social behaviors automatically from data using machine learning, with minimal input from human designers or expensive manual annotation. More generally, he is interested in artificial intelligence, robotics, and linguistics. In the past, he was a research intern at Hiroshi Ishiguro Laboratories, Kyoto, Japan and a research assistant at the Language and Interaction Research group at Michigan State University, USA. He graduated with a BS in computer science and BA in linguistics / Japanese language from MSU in 2013, an MS in computer science from MSU in 2015, and a PhD in human-robot interaction from Osaka University in 2019.
Aurélie Clodic is Research Engineer at LAAS (PhD in robotics (2007), Bachelor in Psychology (2018)). Her research aims to study human-robot collaborative task achievement as well as robotics architecture design (focused on decision-making and supervision. Her recent contributions involved on-line quality of interaction measurement, knowledge base reasoning through ontology management as well as situation assessment. She is the principal investigator of the “Toward a Framework for Joint Action” workshop series (ła.sciencesconf.org). Where she leads a dialog with psychologists and philosophers. She is part of the ANITI institute where she is responsible for the Robotics theme. She contributed in several national (ANR MaRDi, JointAc-tion4HRI) and European (COGNIRON (FP6), SAPHARI (FP7), MuMMER (H2020)) projects. She is the French PI of the ANR trilateral German-French-Japanese AI4HRI project. She is responsible for LAAS of the ANR PRCI ELSA (Effective Learning of Social Affordance) and ANR ASTRID DISCUTER (about Interactive Dialog) projects.
Guillaume Sarthou is a Postdoctoral researcher in Robotics at the Institute for Artificial Intelligence of Bremen, Germany. He received his PhD in robotics in 2021 for which he focused on knowledge representation and exploitation for Human-Robot Interaction. The work of his thesis was included in several projects: JointAction4HRI from the ANR-16-CE33-0017 and the MultiModal Mall Entertainment Robot (MuMMER Project) from Horizon 2020 program. His research interests are about cognitive architecture applied to Human-Robot Interaction in general going from the assessment of the situation to symbolic task planning with a strong link to the knowledge representation of both the robot and the humans it interacts with.
Rachid Alami is Senior Scientist at LAAS-CNRS. He received an engineer diploma in computer science in 1978 from ENSEEIHT, a Ph.D in Robotics in 1983 from Institut National Polytechnique and a Habilitation HDR in 1996 from Paul Sabatier University. He contributed and took important responsibilities in several national, European and international re-search and/or collaborative projects (EUREKA: FAMOS, AMR and I-ARES projects, ESPRIT: MARTHA, PROMotion, ECLA, IST: COMETS, IST FP6 projects: COGNIRON, URUS, PHRIENDS, and FP7 projects: CHRIS, SAPHARI, ARCAS, SPENCER, H2020: MuMMER, France: ARA, VAP-RISP for planetary rovers, PROMIP, several ANR projects). His main research contributions fall in the fields of robot decisional and control architectures, task and motion planning, multi-robot cooperation, and human-robot interaction. Since 2019 he holds the Academic Chair on Cognitive and Interactive Robotics at the Artificial and Natural Intelligence Toulouse Institute (ANITI).
Takayuki Kanda is a professor in Informatics at Kyoto University, Japan. He is also a Visiting Group Leader at ATR Intelligent Robotics and Communication Laboratories, Kyoto, Japan. He received his B. Eng, M. Eng, and Ph.D. degrees in computer science from Kyoto University, Kyoto, Japan, in 1998, 2000, and 2003, respectively. He is one of the starting members of Communication Robots project at ATR. He has developed a communication robot, Robovie, and applied it in daily situations, such as peer-tutor in an elementary school and a museum exhibit guide. His research interests include human-robot interaction, interactive humanoid robots, and field trials.
Dražen Brščić is an associate professor at the Department of Social Informatics at Kyoto University, Kyoto, Japan. He received his PhD degree from Tokyo University, Tokyo, Japan. He was Senior Research Assistant at Institute of Automatic Control Engineering of Technische Universität München, Munich, Germany (from 2008 to 2010). He was Research Scientist at the Intelligent Robotics and Communication Laboratories (IRC) of the Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan (from 2011-2016). He was Assistant Professor of the University of Rijeka, Faculty of Engineering (from 2016-2019). He was Assistant Professor at the Kyoto University, Graduate School of Informatics, Department of Social Informatics (from 2019-2020). His research interests include, People-tracking, Localization, Mobile Robotics and Human-Robot Interaction.
Michael Beetz is a professor of Computer Science at the Faculty for Mathematics & Informatics of the University Bremen and head of the Institute for Artificial Intelligence (IAI). IAI investigates AI-based control methods for robotic agents, with a focus on human-scale everyday manipulation tasks. With his open EASE, a web-based knowledge service providing robot and human activity data, he aims at improving interoperability in robotics and lowering the barriers for robot programming. Due to this the IAI group provides most of its results as open-source software, primarily in the ROS software library. He received his diploma degree in Computer Science with distinction from the University of Kaiserslautern. His MSc, MPhil, and PhD degrees were awarded by Yale University in 1993, 1994, and 1996 and his Venia Legendi from the University of Bonn in 2000. Michael Beetz was a member of the steering committee of the European network of excellence in AI planning (PLANET) and coordinating the research area “robot planning”. He is associate editor of the AI Journal and the coordinator of the German collaborative research centre EASE (Everyday Activity Science and Engineering, since 2017). His research interests include plan-based control of robotic agents, knowledge processing and representation for robots, integrated robot learning, and cognitive perception. In 2019, he received an honorary degree from the University of Örebro for his longstanding co-operation and exceptional, international research.
Mona Abdel-Keream is a Ph.D. student at the Institute of Artificial Intelligence (IAI) in Bremen University, Bremen, Germany. She received her Master’s degree from Fachhochschule Technikum Vienna, Austria in 2017. She did several internships, at CogVis (Cognitive Computer vision) active and assisted living technology, Vienna, Austria (Jan – May 2015); and at Artificial Hands Lab, The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy (Dec – May 2017). Her research interests are development and learning from Human-Robot Interaction (HRI) in simulation, Virtual reality HRI development, AI Reasoning for HRI, cognitive robotics and HRI.