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Vorträge

Learning Control for Intelligent Physical Systems

Talk
  • 13 July 2018 • 14:15 14:45
  • Dr. Sebastian Trimpe
  • MPI-IS, Stuttgart, Lecture Hall 2 D5

Modern technology allows us to collect, process, and share more data than ever before. This data revolution opens up new ways to design control and learning algorithms, which will form the algorithmic foundation for future intelligent systems that shall act autonomously in the physical world. Starting from a discussion of the special challenges when combining machine learning and control, I will present some of our recent research in this exciting area. Using the example of the Apollo robot learning to balance a stick in its hand, I will explain how intelligent agents can learn new behavior from just a few experimental trails. I will also discuss the need for theoretical guarantees in learning-based control, and how we can obtain them by combining learning and control theory.

Organizers: Katherine Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler


Household Assistants: the Path from the Care-o-bot Vision to First Products

Talk
  • 13 July 2018 • 14:45 15:15
  • Dr. Martin Hägele
  • MPI-IS, Stuttgart, Lecture Hall 2 D5

In 1995 Fraunhofer IPA embarked on a mission towards designing a personal robot assistant for everyday tasks. In the following years Care-O-bot developed into a long-term experiment for exploring and demonstrating new robot technologies and future product visions. The recent fourth generation of the Care-O-bot, introduced in 2014 aimed at designing an integrated system which addressed a number of innovations such as modularity, “low-cost” by making use of new manufacturing processes, and advanced human-user interaction. Some 15 systems were built and the intellectual property (IP) generated by over 20 years of research was recently licensed to a start-up. The presentation will review the path from an experimental platform for building up expertise in various robotic disciplines to recent pilot applications based on the now commercial Care-O-bot hardware.

Organizers: Katherine Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler



The Critical Role of Atoms at Surfaces and Interfaces: Do we really have control? Can we?

Talk
  • 13 July 2018 • 15:45 16:15
  • Prof. Dr. Dawn Bonnell
  • MPI-IS, Stuttgart, Lecture Hall 2 D5

With the ubiquity of catalyzed reactions in manufacturing, the emergence of the device laden internet of things, and global challenges with respect to water and energy, it has never been more important to understand atomic interactions in the functional materials that can provide solutions in these spaces.

Organizers: Katherine Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler


Interactive Visualization – A Key Discipline for Big Data Analysis

Talk
  • 13 July 2018 • 15:00 15:30
  • Prof. Dr. Thomas Ertl
  • MPI-IS, Stuttgart, Lecture Hall 2 D5

Big Data has become the general term relating to the benefits and threats which result from the huge amount of data collected in all parts of society. While data acquisition, storage and access are relevant technical aspects, the analysis of the collected data turns out to be at the core of the Big Data challenge. Automatic data mining and information retrieval techniques have made much progress but many application scenarios remain in which the human in the loop plays an essential role. Consequently, interactive visualization techniques have become a key discipline of Big Data analysis and the field is reaching out to many new application domains. This talk will give examples from current visualization research projects at the University of Stuttgart demonstrating the thematic breadth of application scenarios and the technical depth of the employed methods. We will cover advances in scientific visualization of fields and particles, visual analytics of document collections and movement patterns as well as cognitive aspects.

Organizers: Katherine Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler


Imitation of Human Motion Planning

Talk
  • 27 July 2018 • 12:00 12:45
  • Jim Mainprice
  • N3.022 (Aquarium)

Humans act upon their environment through motion, the ability to plan their movements is therefore an essential component of their autonomy. In recent decades, motion planning has been widely studied in robotics and computer graphics. Nevertheless robots still fail to achieve human reactivity and coordination. The need for more efficient motion planning algorithms has been present through out my own research on "human-aware" motion planning, which aims to take the surroundings humans explicitly into account. I believe imitation learning is the key to this particular problem as it allows to learn both, new motion skills and predictive models, two capabilities that are at the heart of "human-aware" robots while simultaneously holding the promise of faster and more reactive motion generation. In this talk I will present my work in this direction.

Haptic Engineering and Science at Multiple Scales

Talk
  • 20 June 2018 • 11:00 12:00
  • Yon Visell, PhD
  • MPI-IS Stuttgart, Heisenbergstr. 3, Room 2P4

I will describe recent research in my lab on haptics and robotics. It has been a longstanding challenge to realize engineering systems that can match the amazing perceptual and motor feats of biological systems for touch, including the human hand. Some of the difficulties of meeting this objective can be traced to our limited understanding of the mechanics, and to the high dimensionality of the signals, and to the multiple length and time scales - physical regimes - involved. An additional source of richness and complication arises from the sensitive dependence of what we feel on what we do, i.e. on the tight coupling between touch-elicited mechanical signals, object contacts, and actions. I will describe research in my lab that has aimed at addressing these challenges, and will explain how the results are guiding the development of new technologies for haptics, wearable computing, and robotics.

Organizers: Katherine Kuchenbecker


Less-artificial intelligence

Talk
  • 18 June 2018 • 15:00 16:00
  • Prof. Dr. Matthias Bethge
  • MPI-IS Stuttgart - 2R04


  • Prof. Andrew Blake
  • Ground Floor Seminar Room N0.002

Organizers: Ahmed Osman


Learning Representations for Hyperparameter Transfer Learning

IS Colloquium
  • 11 June 2018 • 11:15 12:15
  • Cédric Archambeau
  • MPI IS Lecture Hall (N0.002)

Bayesian optimization (BO) is a model-based approach for gradient-free black-box function optimization, such as hyperparameter optimization. Typically, BO relies on conventional Gaussian process regression, whose algorithmic complexity is cubic in the number of evaluations. As a result, Gaussian process-based BO cannot leverage large numbers of past function evaluations, for example, to warm-start related BO runs. After a brief intro to BO and an overview of several use cases at Amazon, I will discuss a multi-task adaptive Bayesian linear regression model, whose computational complexity is attractive (linear) in the number of function evaluations and able to leverage information of related black-box functions through a shared deep neural net. Experimental results show that the neural net learns a representation suitable for warm-starting related BO runs and that they can be accelerated when the target black-box function (e.g., validation loss) is learned together with other related signals (e.g., training loss). The proposed method was found to be at least one order of magnitude faster than competing neural network-based methods recently published in the literature. This is joint work with Valerio Perrone, Rodolphe Jenatton, and Matthias Seeger.

Organizers: Isabel Valera


  • Prof. Martin Spindler
  • MPI IS Lecture Hall (N0.002)

In this talk first an introduction to the double machine learning framework is given. This allows inference on parameters in high-dimensional settings. Then, two applications are given, namely transformation models and Gaussian graphical models in high-dimensional settings. Both kind of models are widely used by practitioners. As high-dimensional data sets become more and more available, it is important to allow situations where the number of parameters is large compared to the sample size.


  • Prof. Martin Spindler
  • MPI IS Lecture Hall (N0.002)

In this talk first an introduction to the double machine learning framework is given. This allows inference on parameters in high-dimensional settings. Then, two applications are given, namely transformation models and Gaussian graphical models in high-dimensional settings. Both kind of models are widely used by practitioners. As high-dimensional data sets become more and more available, it is important to allow situations where the number of parameters is large compared to the sample size.

Organizers: Philipp Geiger


  • Dr. Greg Byrnes
  • Room 3P02 - Stuttgart

Gliding evolved at least nine times in mammals. Despite the abundance and diversity of gliding mammals, little is known about their convergent morphology and mechanisms of aerodynamic control. Many gliding animals are capable of impressive and agile aerial behaviors and their flight performance depends on the aerodynamic forces resulting from airflow interacting with a flexible, membranous wing (patagium). Although the mechanisms that gliders use to control dynamic flight are poorly understood, the shape of the gliding membrane (e.g., angle of attack, camber) is likely a primary factor governing the control of the interaction between aerodynamic forces and the animal’s body. Data from field studies of gliding behavior, lab experiments examining membrane shape changes during glides and morphological and materials testing data of gliding membranes will be presented that can aid our understanding of the mechanisms gliding mammals use to control their membranous wings and potentially provide insights into the design of man-made flexible wings.

Organizers: Metin Sitti Ardian Jusufi


Lessons from the visual system to understand (and help) the brain

IS Colloquium
  • 08 June 2018 • 11:00 12:00
  • Prof. Javier Cudeiro
  • MPI-IS lecture hall (N0.002)

Visual perception involves a complex interaction between feedforward and feedback processes. A mechanistic understanding of these processing, and its limitations, is a necessary first step towards elucidating key aspects of perceptual functions and dysfunctions. In this talk, I will review our ongoing effort towards the understanding of how feedback visual processing operates at the level of the thalamus, a dynamic relay station halfway between the retina and the cortex. I will present experimental evidence from several recent electrophysiology studies performed on subjects engaged in visual detection tasks. The results show that modulatory driving provided by top-down processes (the feedback from primary visual cortex) critically influences the ongoing thalamic activity and shapes the message to be delivered to the cortex. When neuromodulatory techniques (Transcranial Magnetic Stimulation or static magnetic fields) are used to transiently disrupt cortical activity two very interesting effects show up: (1) alterations in stimulus detection and (2) the spatial properties of thalamic receptive fields are dramatically modified. Finally, I will show how sensory information can be a powerful tool to interact with the motor system and re-organize altered patterns of movement in neurological disorders such as Parkinson's disease.

Organizers: Daniel Cudeiro


  • Dr. Hadi Eghlidi
  • MPI-IS Stuttgart, Room 5H7

Investigations and control of biological and synthetic nanoscopic species in liquids at the ultimate resolution of single entity, are important in diverse fields such as biology, medicine, physics, chemistry and emerging field of nanorobotics. Progress made to date on trapping and/or manipulating nanoscopic objects includes methods that use permanently imposed force fields of various kinds, such as optical, electrical and magnetic forces, to counteract their inherent Brownian motion.

Organizers: Peer Fischer Ardian Jusufi


  • Wenzhen Yuan
  • MPI-IS Stuttgart, Heisenbergstr. 3, Room 2P4

Why cannot the current robots act intelligently in the real-world environment? A major challenge lies in the lack of adequate tactile sensing technologies. Robots need tactile sensing to understand the physical environment, and detect the contact states during manipulation. Progress requires advances in the sensing hardware, but also advances in the software that can exploit the tactile signals. We developed a high-resolution tactile sensor, GelSight, which measures the geometry and traction field of the contact surface. For interpreting the high-resolution tactile signal, we utilize both traditional statistical models and deep neural networks. I will describe my research on both exploration and manipulation. For exploration, I use active touch to estimate the physical properties of the objects. The work has included learning the hardness of artificial objects, as well as estimating the general properties of natural objects via autonomous tactile exploration. For manipulation, I study the robot’s ability to detect slip or incipient slip with tactile sensing during grasping. The research helps robots to better understand and flexibly interact with the physical world.

Organizers: Katherine Kuchenbecker