Cooperative Systems

Cooperative Control Systems

Vision

How will automation interact with humans in the future?

How to create synergies between humans and machines in the context of Industry 4.0?

The research group Cooperative Systems develops a framework for modeling and control of interactions between humans and machines. The individual strengths of human and machine are combined to achieve high performance systems, ready to meet future challenges of automatization. The fields of applications are e.g. Advanced Driver Assistance Systems, Robotics, Medical Technologies and Aerospace Engineering.

Cooperative Control Loop

Cooperative Control Loop

Modeling and Identification

The modeling of cooperative systems forms the basis of automation design for cooperative scenarios. In this context, uncertainties in perception and action need to be considered. Furthermore, semantics enable a strategic description of the interaction. Moreover, the identification of human behavior is essential in automation design.

Control Synthesis

Automation design in a cooperative scenario needs to be capable of a dynamic allocation of authority. Furthermore, it requires the ability to negotiate a common goal with the human. One approach to control cooperative systems is based on game theory and Model Predictive Control (MPC). In order to achieve real-time control, motion primitives are examined.

 

Experiments

Motion Tracking is used in various scenarios to measure human motion and validate identification methods.

An Advanced Driving Simulator with haptic feedback human machine interfaces was developed at the IRS. It is used to validate cooperative control methods in the context of advanced driver assistance systems.

A newly developed Ball-on-Plate experiment will be used to apply cooperative identification and control methods in a highly dynamical scenario.

Staff

Jairo Inga Charaja

Head of Research Group

Research Interest:
Identification of Human Behavior in Cooperative Scenarios

   

Balint Varga

Research Associate

Research Interest:
Cooperative control of mobile machinery

Julian Schneider

Research Associate

Research Interest:
Multi level connection for the consistent design of cooperative human-machine systems

Florian Köpf

Research Associate

Research Interest:
Design of Cooperative Control Considering Uncertainties

Simon Rothfuß

Research Associate

Research Interest:
Modeling of Cooperative Goal Negotiation

Esther Bischoff

Research Associate

Research Interest:

Christian Braun

Research Associate

Research Interest:
Shared control of heterogenous robot swarms

Philipp Karg

Research Associate

Research Interest:
Modeling and Identification in Cooperative Human-Machine Scenarios

Xin Ye

Research Associate

Research Interest:
Cooperation of Coupled Multi-Robot Systems

Sean Kille

Research Associate

Research Interest:
 

   

Student Assistants

Manuel Hess

Betreuung des Fahrsimulators

Michael Meyling

Entwicklung eines Human-Machine-Interfaces für Multi-Roboter-Systeme

Recent job offers for student assistants can be found here.

Bachelor and Master Students

Karl Handwerker

Bachelor Thesis

Manöverplanung für ein wandlungsfähiges Multi-Roboter-Fertigungssystem

Matthias Ammann

Master Thesis

Entwicklung und Analyse von Verfahren zur Adaption des Automatisierungsgrades von Belief-Space Methoden

Da Huang

Master Thesis

Identifikation kooperativer Regelungssysteme auf Basis der Theorie dynamischer Potentialspiele

Zhenghong Li

Master Thesis

Entwurf und Implementierung eines LQ-Differentialspielreglers zur Untersuchung effizienter Kooperationsszenarien

Max Günter Grobbel

Master Thesis

Path Integral Inverse Reinforcement Learning

Daniel Flögel

Master Thesis

Cooperative State Estimation for Autonomous Mobile Robots

Saskia Kohn

Master Thesis

Kooperative Koordination heterogener Roboterteams

Jan Rösler

Bachelor Thesis

Aufbau eines ROS-Frameworks mit Simulationsumgebung für haptisch gekoppelte Mensch-Roboter-Bewegungen

Pablo Ramos López

Master Thesis

Automatisiertes Lernen von Zielpräferenzen für die Mensch-Roboter-Interaktion

Frederik Enste

Bachelor Thesis

Simulationsumgebung für die optimale Regelung von Robotersystemen

Xavier Bustamante Zurita

Bachelor Thesis

Entwicklung eines Algorithmus für die kooperative Bahnplanung zwischen Mensch und Roboter

Fan Yang

Master Thesis

Entwicklung eines Aufgabenplaners für einen multifunktionalen Roboter

Daniela Hahn

Master Thesis

Entwicklung von Reoptimierungs-Methoden zur kooperativen Koordination heterogener Multi-Roboter-Teams

Tian Fang

Master Thesis

Entwicklung eines Moduls zur Erkennung von Bewegungsintentionen eines Menschen

Publications


2021
2020
2019
2018
2017
2016
2015
2014
2013