Department Talks
  • Andre Seyfarth
  • MRZ Seminar room

In this presentation a series of conceptual models for describing human and animal locomotion will be presented ranging from standing to walking and running. By subsequently increasing the complexity of the models we show that basic properties of the underlying spring-mass model can be inherited by the more detailed models. Model extensions include the consideration of a rigid trunk (instead of a point mass), non-elastic leg properties (instead of a mass-less leg spring), additional legs (two and four legs), leg masses, leg segments (e.g. a compliantly attached foot) and energy management protocols. Furthermore we propose a methodology to evaluate and refine conceptual models based on the test trilogy. This approach consists of a simulation test, a hardware test and a behavioral comparison of biological experiments with model predictions and hardware models.

Organizers: Ludovic Righetti

  • Auke Ijspeert
  • Max Planck Lecture Hall

Organizers: Ludovic Righetti

Quadrupedal locomotion: a planning & control framework for HyQ

  • 09 March 2015 • 11:00 am 12:00 am
  • Ioannis Havoutis
  • AMD seminar room (TTR building first floor)

It is a great pleasure to invite you to the talk of Ioannis Havoutis (cf. info below) on Monday March 9th at 11h in the AMD seminar room (TTR building, first floor). have a nice week-end, ludovic Quadrupedal animals move with skill, grace and agility. Quadrupedal robots have made tremendous progress in the last few years. In this talk I will give an overview of our work with the Hydraulic Quadruped -HyQ- and present our latest framework for perception, planning and control of quadrupedal locomotion in challenging environments. In addition, I will give a short preview of our work on optimization of dynamic motions, and our future goals.

Organizers: Ludovic Righetti

Introduction to the Scenario Approach

IS Colloquium
  • 19 January 2015 • 11:15 12:15
  • Marco Claudio Campi
  • MPH Lecture Hall, Tübingen

The scenario approach is a broad methodology to deal with decision-making in an uncertain environment. By resorting to observations, or by sampling uncertainty from a given model, one obtains an optimization problem (the scenario problem), whose solution bears precise probabilistic guarantees in relation to new, unseen, situations. The scenario approach opens up new avenues to address data-based problems in learning, identification, finance, and other fields.

Organizers: Sebastian Trimpe

Embedded Optimization for Nonlinear Model Predictive Control

IS Colloquium
  • 19 May 2014 • 10:15 11:30
  • Prof. Moritz Diehl
  • Max Planck House Lecture Hall

This talk shows how embedded optimization - i.e. autonomous optimization algorithms receiving data, solving problems, and sending answers continuously - are able to address challenging control problems. When nonlinear differential equation models are used to predict and optimize future system behaviour, one speaks of Nonlinear Model Predictive Control (NMPC).The talk presents experimental applications of NMPC to time and energy optimal control of mechatronic systems and discusses some of the algorithmic tricks that make NMPC optimization rates up to 1 MHz possible. Finally, we present on particular challenging application, tethered flight for airborne wind energy systems.

Organizers: Sebastian Trimpe