Speakers
The first part of the event (tutorial) will be given mainly by the organizers, while the second part (workshop) by the following invited speakers.
Dr. Ajoudani, Arash
Bio: Dr. Arash Ajoudani is a tenured senior scientist at the Italian Institute of Technology (IIT), where he leads the Human-Robot Interfaces and physical Interaction (HRI²) laboratory. He also coordinates the Robotics for Manufacturing (R4M) lab of the Leonardo labs, and is a principal investigator of the IIT-Intellimech JOiiNT lab. He received his PhD degree in Robotics and Automation from University of Pisa and IIT in 2014. He is a scholar of the European Lab for Learning and Intelligent Systems (ELLIS). His main research interests are in physical human-robot interaction, mobile manipulation, robust and adaptive control, assistive robotics, and tele-robotics.
Talk title: Towards Context-Aware Robot Interaction Autonomy [ Virtual talk ]
Talk abstract: Nowadays, robots are expected to enter various application scenarios and interact with unknown and dynamically changing environments. This highlights the need for creating autonomous robot behaviors to explore such environments, identify their characteristics and adapt, and build knowledge for future interactions. To respond to this need, in this talk I will present methods to enable context-aware and adaptive interactions between robots and uncertain environments. The core of this framework is a self-tuning impedance controller that regulates robot quasi-static parameters, i.e., stiffness and damping, based on the robot's sensory data and vision. The tuning of the parameters is achieved only in the direction(s) of interaction or movement, by distinguishing expected interactions from external disturbances.
Dr. Albu-Schäffer, Alin
Bio: Dr. Alin Albu-Schäffer completed his studies in electrical engineering at TU Timisoara in Romania in 1993 and obtained his PhD in 2002 from TUM. Since 1995 he has been a researcher at the German Aerospace Center (DLR) where he has headed the Department of Mechatronic Components and Systems since 2009. In 2012 Professor Albu-Schäffer was simultaneously appointed full professor at TUM in the Department of Computer Science and director of the Institute of Robotics and Mechatronics at DLR. He is currently on leave of absence from TUM on account of his role as institute director at DLR. Despite this he continues to teach a limited number of courses at TUM and heads a small research group focusing on robotics.
The research field of Professor Albu-Schäffer (b. 1968) is in the area of design, sensor based programming and control of complex robotic systems for manipulation and locomotion. In particular, he is interested in robots and algorithms for direct, safe and intuitive interaction with humans and unknown environments. A major emphasis of this research work is the processing and feedback of heterogeneous sensor information within ultra-lightweight, compliant robots inspired by biological systems. The main areas of application are robotic assistance in space, industrial manufacturing, health-care and home environments.
Keppler, Manuel
Bio: Manuel Keppler received the Dipl.Ing. degree in mechanical engineering with a focus on control theory from Technical University of Vienna, Vienna, Austria, in 2014. Since then, he has been with the German Aerospace Center (DLR), Institute of Robotics and Mechatronics, Wessling, Germanyn where he leads control developments for VSA robots. He is also a PhD candidate at Technical University of Munich working on Impedance and motion tracking control of variable stiffness robots. In 2019 he did a research stay in Rome in collaboration with Prof. Alessandro De Luca from La Sapienza university working on time-optimal control of elastic joint robots.
His current research interests include natural motion and impedance control of compliant robots, design and control of elastic legs with the goal of achieving energy-efficient locomotion, and nonlinear control of underactuated Lagrangian systems.
Talk title: VIA robots: Lessons leaned on Design, Control and Exploitation of Nonlinear Modes
Talk abstract: TBD
Dr. Adrià Colomé is a Postdoctoral Researcher at the Insistut de Robòtica i Informàtica Industrial in Barcelona. His research and interests are on robot motion learning and control, with real applications in domestic environments and to cloth manipulation. Adrià has published research articles on dimensionality reduction techniques applied to robot motion learning and control, robot motion characterization, reinforcement learning, or variable impedance control.
Colomé recieved his Licenciate degree in Mathematics in 2009, as well as a degree in Industrial Engineering in the same year, both at the Universitat Politècnica de Catalunya (UPC). After pursuing a Master in Robotics, he received his PhD also at the UPC in 2017, for which he was awarded with the Robotnik prize to the best Spanish robotics PhD thesis, and was a finalist for the Georges Giralt award to the best European thesis in robotics in the same year.
Talk title: Learning Variable Impedance through Perturbations
Talk abstract: TBD
Dr. Olson, Gina
Bio: Dr. Gina Olson is a postdoctoral research scientist working in Prof. Carmel Majidi’s Soft Machines Lab at Carnegie Mellon University. She earned her doctorate in Robotics and Mechanical Engineering at Oregon State University’s Collaborative Robotics and Intelligent Systems Institute, where she was advised by Dr. Yiğit Mengüç and Prof. Julie A. Adams. Her current research interests are the development and study of the soft and compliant structures within soft robots, and her past research interests lie in the area of deployable space structures for small satellites. She previously worked as a Technical Lead Engineer at Meggitt Polymers and Composites, where she led the development and certification of fire seals for aircraft engines and learned the intricacies of manufacturing at a production level. Dr. Olson’s future research directions are guided by the desire to see capable soft robots used in the world.
Talk title: The Influence of Structure on Soft and Compliant Robots [ In-person talk ]
Talk abstract: Soft and compliant robots use geometric and material deformation to absorb impacts, mimic natural motions, mechanically adapt to motion or unevenness and to store and reuse energy. During this talk, I will introduce the concept of compliant robots as active structures, with capabilities and behaviors derived from the type and organization of their active and passive elements. Understanding the core mechanics of these active structures enables rigorous design to meet a particular set of requirements on stiffness, range of motion, etc – or, conversely, to show that a particular design is unlikely to be suitable. I will present my current and prior work on the development and analysis of soft and compliant robotic structures, with a particular focus on the mechanics of soft arms. I will discuss how structure and mechanics affect concepts critical to robotics, such as workspace size, applied force, control and planning.
Dr. Pan, Yongping
Bio: Dr. Yongping Pan received the Ph.D. degree in control theory and control engineering from the South China University of Technology (SCUT), Guangzhou, China in 2011. He was a Control Engineer with the Santak Electronic Company, Ltd., Eaton Group, Shenzhen, China, and the Light Engineer-ing Company, Ltd., Guangzhou from 2007 to 2008. From 2011 to 2013, he was a Research Fellow with the School of Electrical and Electronic Engineering, Nanyang Technological University, Sin-gapore. He is currently a Research Fellow with the Department of Biomedical Engineering, Na-tional University of Singapore, Singapore. He has authored or co-authored over 50 peer-reviewed research papers in journals and conferences. His research interests include automatic control, computational intelligence, and robotics and automation. Dr Pan is an Associate Editor of the In-ternational Journal of Fuzzy Systems, and serves as a Reviewer for several flagship journals. He was a recipient of the Rockwell Automation Master Scholarship, the GDUT Postgraduate Academ-ic Award in 2006, the SCUT Innovation Fund of Excellent Doctoral Dissertations, and the SCUT Ex-cellent Graduate Student Award in 2010.
Talk title: Composite Learning Tracking and Interaction Control for Compliant Robots [ Virtual talk ]
Talk abstract: Due to the rapid population aging globally, the current trend of robotic research has been shifting from traditional industrial robots that are separated from humans to human-centered robots that coexist, cooperate, and collaborate with humans. A major motivation for introducing compliance to human-centered robots is one of their distinctive features: Physical human-robot interaction. This talk considers compliant robots with flexible joints and highlights our three major results in composite learning control for compliant robots. First, we establish the connection of the human motor learning and control mechanism to adaptive and learning control theory. Second, we propose a composite learning technique to achieve efficient learning from the bioinspired adaptive robot control. Third, we apply composite learning control methods to improve the accuracy, safety, and naturalness of compliant robots. Experiments based on several physical robots are provided to verify the effectiveness and superiority of the proposed methods.
Dr. Righetti, Ludovic
Bio: Ludovic Righetti is an Associate Professor in the Electrical and Computer Engineering Department and in the Mechanical and Aerospace Engineering Department at the Tandon School of Engineering of New York University and a Senior Researcher at the Max-Planck Institute for Intelligent Systems in Germany. He holds an Engineering Diploma in Computer Science and a Doctorate in Science from the Ecole Polytechnique Fédérale de Lausanne. His research focuses on the planning, control and learning of movements for autonomous robots, with a special emphasis on legged locomotion and manipulation.
Talk title: Computing variable impedance schedules to improve contact interactions
Talk abstract: To walk, run, jump or manipulate objects, robots constantly interact with objects and the environment. During these interactions, robots need to exhibit two seemingly contradicting features: 1) they need to be able to reject disturbances, which usually require rather high impedance and 2) they need to handle the uncertainty of contact locations, which require increased compliance. How can one compute a variable impedance profile for robots in contact with their environment that best trades off both requirements? In this talk, I will present our recent work which provides a tentative answer: we can explicitly model disturbances and contact measurement uncertainty and solve an associated stochastic optimal control problem. I will then discuss some of our recent experimental results and current open issues.
Prof. Rus, Daniela
Bio: Daniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science, Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, and Deputy Dean of Research in the Schwarzman College of Computing at MIT. Rus' research interests are in robotics and artificial intelligence. The key focus of her research is to develop the science and engineering of autonomy. Rus is a MacArthur Fellow, a fellow of ACM, AAAI and IEEE, a member of the National Academy of Engineering, and of the American Academy of Arts and Sciences. She is a senior visiting fellow at MITRE Corporation. She is the recipient of the Engelberger Award for robotics and the IEEE RAS Pioneer award. She earned her PhD in Computer Science from Cornell University.
Talk title: TBD
Talk abstract: TBD