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Institute Talks

Learning to Act with Confidence

Talk
  • 23 October 2018 • 12:00 13:00
  • Andreas Krause
  • MPI-IS Tübingen, N0.002

Actively acquiring decision-relevant information is a key capability of intelligent systems, and plays a central role in the scientific process. In this talk I will present research from my group on this topic at the intersection of statistical learning, optimization and decision making. In particular, I will discuss how statistical confidence bounds can guide data acquisition in a principled way to make effective and reliable decisions in a variety of complex domains. I will also discuss several applications, ranging from autonomously guiding wetlab experiments in protein function optimization to safe exploration in robotics.

Control Systems for a Surgical Robot on the Space Station

IS Colloquium
  • 23 October 2018 • 16:30 17:30
  • Chris Macnab
  • MPI-IS Stuttgart, Heisenbergstr. 3, Room 2P4

As part of a proposed design for a surgical robot on the space station, my research group has been asked to look at controls that can provide literally surgical precision. Due to excessive time delay, we envision a system with a local model being controlled by a surgeon while the remote system on the space station follows along in a safe manner. Two of the major design considerations that come into play for the low-level feedback loops on the remote side are 1) the harmonic drives in a robot will cause excessive vibrations in a micro-gravity environment unless active damping strategies are employed and 2) when interacting with a human tissue environment the robot must apply smooth control signals that result in precise positions and forces. Thus, we envision intelligent strategies that utilize nonlinear, adaptive, neural-network, and/or fuzzy control theory as the most suitable. However, space agencies, or their engineering sub-contractors, typically provide gain and phase margin characteristics as requirements to the engineers involved in a control system design, which are normally associated with PID or other traditional linear control schemes. We are currently endeavouring to create intelligent controls that have guaranteed gain and phase margins using the Cerebellar Model Articulation Controller.

Organizers: Katherine Kuchenbecker

Artificial haptic intelligence for human-machine systems

IS Colloquium
  • 24 October 2018 • 11:00 12:00
  • Veronica J. Santos
  • 5H7 at MPI-IS in Stuttgart

The functionality of artificial manipulators could be enhanced by artificial “haptic intelligence” that enables the identification of object features via touch for semi-autonomous decision-making and/or display to a human operator. This could be especially useful when complementary sensory modalities, such as vision, are unavailable. I will highlight past and present work to enhance the functionality of artificial hands in human-machine systems. I will describe efforts to develop multimodal tactile sensor skins, and to teach robots how to haptically perceive salient geometric features such as edges and fingertip-sized bumps and pits using machine learning techniques. I will describe the use of reinforcement learning to teach robots goal-based policies for a functional contour-following task: the closure of a ziplock bag. Our Contextual Multi-Armed Bandits approach tightly couples robot actions to the tactile and proprioceptive consequences of the actions, and selects future actions based on prior experiences, the current context, and a functional task goal. Finally, I will describe current efforts to develop real-time capabilities for the perception of tactile directionality, and to develop models for haptically locating objects buried in granular media. Real-time haptic perception and decision-making capabilities could be used to advance semi-autonomous robot systems and reduce the cognitive burden on human teleoperators of devices ranging from wheelchair-mounted robots to explosive ordnance disposal robots.

Organizers: Katherine Kuchenbecker

Artificial haptic intelligence for human-machine systems

IS Colloquium
  • 25 October 2018 • 11:00 11:00
  • Veronica J. Santos
  • N2.025 at MPI-IS in Tübingen

The functionality of artificial manipulators could be enhanced by artificial “haptic intelligence” that enables the identification of object features via touch for semi-autonomous decision-making and/or display to a human operator. This could be especially useful when complementary sensory modalities, such as vision, are unavailable. I will highlight past and present work to enhance the functionality of artificial hands in human-machine systems. I will describe efforts to develop multimodal tactile sensor skins, and to teach robots how to haptically perceive salient geometric features such as edges and fingertip-sized bumps and pits using machine learning techniques. I will describe the use of reinforcement learning to teach robots goal-based policies for a functional contour-following task: the closure of a ziplock bag. Our Contextual Multi-Armed Bandits approach tightly couples robot actions to the tactile and proprioceptive consequences of the actions, and selects future actions based on prior experiences, the current context, and a functional task goal. Finally, I will describe current efforts to develop real-time capabilities for the perception of tactile directionality, and to develop models for haptically locating objects buried in granular media. Real-time haptic perception and decision-making capabilities could be used to advance semi-autonomous robot systems and reduce the cognitive burden on human teleoperators of devices ranging from wheelchair-mounted robots to explosive ordnance disposal robots.

Organizers: Katherine Kuchenbecker Adam Spiers

TBA

IS Colloquium
  • 28 January 2019 • 3pm 4pm
  • Florian Marquardt

Organizers: Matthias Bauer

  • Carl E. Rasmussen
  • MPI IS Lecture Hall Tübingen

Gaussian Processes are a principled, practical, probabilistic approach to learning in flexible non-parametric models and have found numerous applications in regression, classification, unsupervised learning and reinforcement learning. Inference, learning and prediction can be done exactly on small data sets with Gaussian likelihood. In more realistic application with large scale data and more complicated likelihoods approximations are necessary. The variational framework for approximate inference in Gaussian processes has emerged recently as a highly effective and practical tool. I will review and demonstrate the capabilities of this framework applied to non-linear state space models.

Organizers: Philipp Hennig


  • Weiqiang Chen Ph.D.
  • Stuttgart

Taking advantages of state-of-art micro/nanotechnologies, fascinating functional biomaterials and integrated biosystems, we can address numerous important problems in fundamental biology as well as clinical applications in cancer diagnosis and treatment.

Organizers: Peer Fischer


Modeling anguilliform swimming, robotic swimming

Talk
  • 09 July 2018 • 11:00 12:00
  • Robin Thandiackal
  • 2P4, Stuttgart MPI IS

Exciting talk on modeling anguilliform swimming, robotic testing.

Organizers: Steve Heim Alexander Sproewitz


  • Zeynep Akata
  • S2.014

Clearly explaining a rationale for a classification decision to an end-user can be as important as the decision itself. Existing approaches for deep visual recognition are generally opaque and do not output any justification text; contemporary vision-language models can describe image content but fail to take into account class-discriminative image aspects which justify visual predictions. In this talk, I will present my past and current work on Zero-Shot Learning, Vision and Language for Generative Modeling and Explainable Artificial Intelligence in that (1) how we can generalize the image classification models to the cases when no visual training data is available, (2) how to generate images and image features using detailed visual descriptions, and (3) how our models focus on discriminating properties of the visible object, jointly predict a class label,explain why the predicted label is appropriate for the image whereas another label is not.

Organizers: Andreas Geiger


Structure-Aware Shape Synthesis

Talk
  • 03 July 2018 • 11:00 12:00
  • Elena Balashova (Sizikova)
  • Aquarium N3

Complex shapes can can be summarized using a coarsely defined structure which is consistent and robust across variety of observations. However, existing synthesis techniques do not consider structural decomposition during synthesis, causing generation of implausible or structurally unrealistic shapes. We explore how structure-aware reasoning can benefit existing generative techniques for complex 2D and 3D shapes. We evaluate our methodology on a 3D dataset of chairs and a 2D dataset of typefaces.

Organizers: Sergi Pujades


The Computational Skin. Tactile Perception based on Slip Movements.

IS Colloquium
  • 02 July 2018 • 14:30 15:30
  • Prof. Dr. Cornelius Schwarz
  • MPI-IS Stuttgart, Heisenbergstr. 3, Room 2P4

Touch requires mechanical contact and is governed by the physics of friction. Frictional movements may convert the continuous 3D profile of textural objects into discrete and probabilistic movement events of the viscoelastic integument (skin/hair) called stick-slip movements (slips). This complex transformation may further be determined by the microanatomy and the active movements of the sensing organ. Thus, the integument may realize a computation, transforming the tactile world in a context dependent way - long before it even activates neurons. The possibility that the tactile world is perceived through these ‘fractured goggles’ of friction has been largely ignored by classical perceptual and neuro-scientific work. I will present biomechanical, neuro-scientific, and behavioral work supporting the slip hypothesis.

Organizers: Katherine Kuchenbecker


  • Prof. William W. Hager
  • AMD seminar room (N2.025)

Optimal control problems are often too complex to solve analytically. Computational methods usually replace the continuous infinite dimensional problem by a finite dimensional discrete approximation. The talk will survey classical discretization techniques based on a Runge-Kutta approximation to the differential equations (an h-method) and then introduce recent approximations based on collocation at the roots of orthogonal polynomials (a p-method). The best approximations are often achieved using an hp-framework that combines the best features of both approaches. Numerical results using the GPOPS-II (General Pseudospectral Optimal Control Software package) will be presented.

Organizers: Jia-Jie Zhu


Improving the Gaussian Mechanism for Differential Privacy

IS Colloquium
  • 27 June 2018 • 14:15 15:15
  • Borja de Balle Pigem
  • MPI IS lecture hall (N0.002)

The Gaussian mechanism is an essential building block used in multitude of differentially private data analysis algorithms. In this talk I will revisit the classical analysis of the Gaussian mechanism and show it has several important limitations. For example, our analysis reveals that the variance formula for the original mechanism is far from tight in the high privacy regime and that it cannot be extended to the low privacy regime. We address these limitations by developing a new Gaussian mechanism whose variance is optimally calibrated by solving an equation involving the Gaussian cumulative density function. Our analysis side-steps the use of tail bounds approximations and relies on a novel characterisation of differential privacy that might be of independent interest. We numerically show that analytical calibration removes at least a third of the variance of the noise compared to the classical Gaussian mechanism. We also propose to equip the Gaussian mechanism with a post-processing step based on adaptive denoising estimators by leveraging that the variance of the perturbation is known. Experiments with synthetic and real data show that this denoising step yields dramatic accuracy improvements in the high-dimensional regime. Based on joint work with Y.-X. Wang to appear at ICML 2018. Pre-print: https://arxiv.org/abs/1805.06530

Organizers: Michel Besserve Isabel Valera


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